National Library of Energy BETA

Sample records for gross household income

  1. Loan Programs for Low- and Moderate-Income Households | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer ...

  2. Fact #565: April 6, 2009 Household Gasoline Expenditures by Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Household Gasoline Expenditures by Income Quintile Bar graph showing the household gasoline expenditures by income quintile in the years 1989, 1997, and 2007. For more detailed ...

  3. Loan Programs for Low- and Moderate-Income Households

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014.

  4. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

    Provides state and local policymakers with information on successful approaches to the design and implementation of residential efficiency programs for households ineligible for low-income programs.

  5. Effect of Income on Appliances in U.S. Households, The

    Reports and Publications (EIA)

    2004-01-01

    Entails how people live, the factors that cause the most differences in home lifestyle, including energy use in geographic location, socioeconomics and household income.

  6. Forum on Enhancing the Delivery of Energy Efficiency to Middle Income Households: Discussion Summary

    SciTech Connect (OSTI)

    none,

    2012-09-20

    Summarizes discussions and recommendations from a forum for practitioners and policymakers aiming to strengthen residential energy efficiency program design and delivery for middle income households.

  7. EPA Webinar: Bringing Energy Efficiency and Renewable Housing to Low-Income Households

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency, this webinar will explore the topic of linking and leveraging energy efficiency and renewable energy programs for limited-income households, including the need to coordinate with other energy assistance programs.

  8. Table HC1-3a. Housing Unit Characteristics by Household Income,

    U.S. Energy Information Administration (EIA) Indexed Site

    3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Census Region and Division Northeast

  9. "Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005"

    U.S. Energy Information Administration (EIA) Indexed Site

    0 Home Appliances Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Usage Indicators"

  10. "Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005"

    U.S. Energy Information Administration (EIA) Indexed Site

    2 Home Electronics Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Electronics Usage Indicators"

  11. "Table HC7.5 Space Heating Usage Indicators by Household Income, 2005"

    U.S. Energy Information Administration (EIA) Indexed Site

    5 Space Heating Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Usage Indicators" "Total U.S. Housing

  12. The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-06-01

    In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

  13. Weatherization assistance for low-income households: An evaluation of local program performance

    SciTech Connect (OSTI)

    Schweitzer, M.; Rayner, S.; Wolfe, A.K.; Mason, T.W.; Ragins, B.R.; Cartor, R.A.

    1987-08-01

    The US Department of Energy's Weatherization Assistance Program (WAP) funds local agencies to provide weatherization services to low-income households. This report describes the most salient features of this program, examines relationships between organization and program outcomes, and presents recommendations for the program's further development. Data were collected by written surveys administered to local weatherization agencies, a telephone survey of 38 states and eight DOE support offices, and site visits to selected local agencies. Locally controlled factors found to be significantly related to program performance include the amount of the weatherization director's time spent on program administration, the use of established client selection criteria, the frequency of evaluation of local goal attainment, and the type of weatherization crews used. Factors controlled at the state or federal levels that influence program performance include delays in state reimbursements of local agency expenditures and local flexibility in the choice of weatherization measures. Data-gathering difficulties experienced during this project indicate a need for possible improvements in goal-setting and record-keeping procedures.

  14. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    3 Household Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Household Characteristics"

  15. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    1 Home Electronics Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Electronics Characteristics"

  16. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    2 Living Space Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Living Space Characteristics"

  17. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    Housing Unit Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Housing Unit Characteristics"

  18. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    4 Space Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Space Heating Characteristics"

  19. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    6 Air Conditioning Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air Conditioning Characteristics"

  20. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    7 Air-Conditioning Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Air-Conditioning Usage Indicators"

  1. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    HC7.9 Home Appliances Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Home Appliances Characteristics" "Total

  2. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    3 Lighting Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Lighting Usage Indicators" "Total U.S. Housing

  3. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

    U.S. Energy Information Administration (EIA) Indexed Site

    8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Water Heating Characteristics"

  4. BENTON PUD LOW INCOME CONSERVATION PROGRAM

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    result in a preference being given to households with incomes below 125% of Federal Poverty Guidelines (FPG) Upper low income households with incomes between 125 and 200%...

  5. usage_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  6. housingunit_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  7. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  8. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  9. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... Income Relative to Poverty Line Below 100 Percent ...... 15.0 13.2 1.8 Q ...

  10. Samantha Gross

    Broader source: Energy.gov [DOE]

    Samantha Gross is the Director for International Climate and Clean Energy at the Office of International Affairs in the U.S. Department of Energy. She directs U.S. activities under the Clean Energy...

  11. Targeted Marketing and Program Design for Low- and Moderate-Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Targeted Marketing and Program Design for Low- and Moderate-Income Households Targeted Marketing and Program Design for Low- and Moderate-Income Households Better Buildings ...

  12. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  13. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State income

  14. Targeted Marketing and Program Design for Low- and Moderate-Income

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Households | Department of Energy Targeted Marketing and Program Design for Low- and Moderate-Income Households Targeted Marketing and Program Design for Low- and Moderate-Income Households Better Buildings Neighborhood Program Low- / Moderate-Income Peer Exchange Call: Targeted Marketing and Program Design for Low- and Moderate-Income Households, Call Slides and Discussion Summary, October 11, 2011. PDF icon Call Slides and Discussion Summary More Documents & Publications Loan Programs

  15. Household magnets

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Household magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to put it back

  16. grossWCI.dvi

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Nuclear multifragmentation, Its relation to general physics A rich test-ground of the fundamentals of statistical mechanics. D.H.E. Gross 1 Hahn-Meitner Institute Glienickerstr. 100 14109 Berlin, Germany gross@hmi.de; http://www.hmi.de/people/gross/ 2 Freie Universit¨ at Berlin, Fachbereich Physik. Received: date / Revised version: date Abstract. Heat can flow from cold to hot at any phase separation, even in macroscopic systems. Therefore also Lynden-Bell's famous gravo-thermal catastrophe [1]

  17. EIA - Household Transportation report: Household Vehicles Energy...

    U.S. Energy Information Administration (EIA) Indexed Site

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series....

  18. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    Program Definitions DOE Weatherization: Department of Energy's Weatherization Assistance Program DOE Weatherization Eligible Households: Households with incomes at or below 125% of the Federal poverty level, which varies by family size; however, a State may instead elect to use the LIHEAP income standard if its State LIHEAP income standard is at least 125% of the Federal poverty level. Data listed in this chapter include previously weatherized units. DOE Weatherization Eligible Households are a

  19. Michael Gross | Photosynthetic Antenna Research Center

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Michael Gross Michael Gross Michael Gross Principal Investigator E-mail: mgross@wustl.edu Phone: (314) 935-4814 Website: Washington University in St. Louis Principal Investigator...

  20. BC Hydro Brings Energy Savings to Low-Income Families in Canada...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    BC Hydro Brings Energy Savings to Low-Income Families in Canada BC Hydro Brings Energy Savings to Low-Income Families in Canada The number of British Columbia, Canada, households ...

  1. ,"Alaska Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    "Back to Contents","Data 1: Alaska Natural Gas Gross Withdrawals and Production" ... "Date","Alaska Natural Gas Gross Withdrawals (MMcf)","Alaska Natural ...

  2. ,"Arkansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    to Contents","Data 1: Arkansas Natural Gas Gross Withdrawals and Production" ... "Date","Arkansas Natural Gas Gross Withdrawals (MMcf)","Arkansas Natural ...

  3. Texas--onshore Natural Gas Gross Withdrawals (Million Cubic Feet...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Texas--onshore Natural Gas Gross Withdrawals ... Referring Pages: Natural Gas Gross Withdrawals Texas Onshore Natural Gas Gross Withdrawals ...

  4. Texas--State Offshore Natural Gas Gross Withdrawals (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Texas--State Offshore Natural Gas Gross Withdrawals ... Offshore Gross Withdrawals of Natural Gas Natural Gas Gross Withdrawals Texas State ...

  5. Texas Natural Gas Gross Withdrawals Total Offshore (Million Cubic...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals Total Offshore (Million Cubic Feet) Texas Natural Gas Gross Withdrawals ... Offshore Gross Withdrawals of Natural Gas Natural Gas Gross Withdrawals Texas Offshore ...

  6. Try This: Household Magnets

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Household Magnets Household Magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to

  7. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-01-01

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  8. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    Teotia, A.; Poyer, D.

    1991-12-31

    Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

  9. ,"West Virginia Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    AM" "Back to Contents","Data 1: West Virginia Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010WV2" "Date","West Virginia Natural Gas Gross Withdrawals (MMcf)" ...

  10. David J. Gross and the Strong Force

    Office of Scientific and Technical Information (OSTI)

    ... Nobel Laureate Says Physics Is in Need of a Revolution Videos: Nobel Lecture by David J. Gross, nobelprize.org (video) Interview with David J. Gross, nobelprize.org (video) ...

  11. ,"New Mexico Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    7:01:11 AM" "Back to Contents","Data 1: New Mexico Natural Gas Gross Withdrawals (MMcf)" "Sourcekey","N9010NM2" "Date","New Mexico Natural Gas Gross Withdrawals (MMcf)" ...

  12. Sofia Mancheno-Gross | Department of Energy

    Energy Savers [EERE]

    Sofia Mancheno-Gross Sofia Mancheno-Gross Sofia Mancheno-Gross - Senior Communications Lead Sofia specializes in Communications strategies on behalf of the Office of Energy Efficiency and Renewable Energy. Most Recent Guía Ahorre Energía: Consejos sobre el ahorro de dinero y energía en el hogar November 14

  13. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from ...

  14. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Referring Pages: Natural Gas Gross Withdrawals from Shale Gas Wells Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from ...

  15. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    292016 Next Release Date: 2292016 Referring Pages: Natural Gas Gross Withdrawals from Oil Wells Missouri Natural Gas Gross Withdrawals and Production Natural Gas Gross...

  16. Table 5.9. U.S. Average Vehicle-Miles Traveled by Family Income...

    U.S. Energy Information Administration (EIA) Indexed Site

    1993 Household Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

  17. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

  18. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    2 Energy Burden Definitions Energy burden is an important statistic for policy makers who are considering the need for energy assistance. Energy burden can be defined broadly as the burden placed on household incomes by the cost of energy, or more simply, the ratio of energy expenditures to household income. However, there are different ways to compute energy burden, and different interpretations and uses of the energy burden statistics. DOE Weatherization primarily uses mean individual burden

  19. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) Indexed Site

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  20. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) Indexed Site

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991...

  1. ,"Ohio Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151991" ,"Release ...

  2. ,"Wyoming Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  3. ,"Utah Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  4. ,"Texas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  5. ,"Michigan Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  6. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ...ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  7. ,"Montana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  8. ,"Oregon Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151991" ,"Release ...

  9. David J. Gross and the Strong Force

    Office of Scientific and Technical Information (OSTI)

    published their proposal simultaneously with H. David Politzer, a graduate student at Harvard University who independently came up with the same idea. ... The discovery of Gross,...

  10. ,"Texas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. ,"Kansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  13. ,"Kentucky Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  14. ,"Oregon Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301979" ,"Release...

  15. ,"Virginia Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  16. ,"Missouri Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  17. ,"Illinois Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  18. ,"Florida Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  19. ,"Utah Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  20. ,"Indiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  1. ,"Nevada Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301991" ,"Release...

  2. ,"Montana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  3. ,"Ohio Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  4. ,"California Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  5. ,"Mississippi Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  6. ,"Nebraska Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  7. ,"Michigan Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  8. ,"Tennessee Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  9. ,"Oklahoma Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  10. ,"Wyoming Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. ,"Maryland Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  12. ,"Louisiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  13. ,"Colorado Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  14. BC Hydro Brings Energy Savings to Low-Income Families in Canada |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy BC Hydro Brings Energy Savings to Low-Income Families in Canada BC Hydro Brings Energy Savings to Low-Income Families in Canada The number of British Columbia, Canada, households eligible for Better Buildings Residential Network member BC Hydro's Energy Conservation Assistance Program (ECAP) just doubled. British Columbia Energy Minister Bill Bennett recently announced an increase in the low-income qualification cutoff for BC Hydro's free home energy-saving kits and

  15. Next Generation Household Refrigerator | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  16. Strategies for Collecting Household Energy Data | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for ...

  17. Household Vehicles Energy Use Cover Page

    U.S. Energy Information Administration (EIA) Indexed Site

    Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback * PrivacySecurity *...

  18. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1

  19. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1

  20. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...

  1. char_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC2-1a. Household Characteristics by ...

  2. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  3. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    ......... 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  4. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  5. homeoffice_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    ......... 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  6. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    ... location is over a period of one year, relative to a base temperature of 65 degrees Fahrenheit. A household is assigned to a climate zone according to the 30-year average annual ...

  7. Household Vehicles Energy Consumption 1991

    U.S. Energy Information Administration (EIA) Indexed Site

    16.8 17.4 18.6 18.9 1.7 2.2 0.6 1.5 Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 15 Vehicle Miles Traveled per Vehicle (Thousand) . . . . . . . . ....

  8. ac_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated ... New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditi...

  9. ac_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to ...

  10. ac_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total ...

  11. ac_household2001.pdf

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    8a. Air Conditioning by UrbanRural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total UrbanRural Location 1 RSE Row Factors City ...

  12. Cover Page of Household Vehicles Energy Use: Latest Data & Trends

    Gasoline and Diesel Fuel Update (EIA)

    Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

  13. ,"Alaska Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"4292016 6:48:19 AM" "Back to Contents","Data 1: Alaska Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AK2","N9011AK2","N9012AK2","NGME...

  14. ,"Arkansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"4292016 6:48:21 AM" "Back to Contents","Data 1: Arkansas Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AR2","N9011AR2","N9012AR2","NGME...

  15. ,"Arizona Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"4292016 6:48:23 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AZ2","N9011AZ2","N9012AZ2","NGME...

  16. ,"Arizona Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    ,,"(202) 586-8800",,,"4292016 6:48:22 AM" "Back to Contents","Data 1: Arizona Natural Gas Gross Withdrawals and Production" "Sourcekey","N9010AZ2","N9011AZ2","N9012AZ2","NGME...

  17. Quantification of the Potential Gross Economic Impacts of Five...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios Quantification of the Potential Gross Economic Impacts of Five Methane Reduction Scenarios ...

  18. Property:DailyOpWaterUseGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name DailyOpWaterUseGross Property Type Number Description Daily Operation Water Use (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProperty:...

  19. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... definition. 2 Below 150 percent of poverty line or 60 percent of median State ...

  20. Low Income Efficiency

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Materials Meeting 5, November 5, 2015 in Portland, Oregon Agenda BPA Low Income Benchmarking and October 2015 IM Updates Presentation Side by Side Comparison of BPA Measures...

  1. Resource handbook for low-income residential retrofits

    SciTech Connect (OSTI)

    Callaway, J.W.; Brenchley, D.L.; Davis, L.J.; Ivey, D.L.; Smith, S.A.; Westergard, E.J.

    1987-04-01

    The purpose of the handbook is to provide technical assistance to state grantees participating in the Partnerships in Low-Income Residential Retrofit (PILIRR) Program. PILIRR is a demonstration program aimed at identifying innovative, successful approaches to developing public and private support for weatherization of low-income households. The program reflects the basic concept that responsibility for financial support for conservation activities such as low-income residential retrofitting is likely to gradually shift from the DOE to the states and the private sector. In preparing the handbook, PNL staff surveyed over 50 programs that provide assistance to low-income residents. The survey provided information on factors that contribute to successful programs. PNL also studied the winning PILIRR proposals (from the states of Florida, Iowa, Kentucky, Oklahoma and Washington) and identified the approaches proposed and the type of information that would be most helpful in implementing these approaches.

  2. Federal options for low-income electricity policy

    SciTech Connect (OSTI)

    Baxter, L.W.

    1998-06-01

    Protection of low-income consumers remains an important public policy concern in a restructuring electricity industry. Policies are needed to ensure that low-income households have enough affordable electricity to protect their health and safety, and that they are not victimized by unscrupulous suppliers. In this paper, the author presents three broad federal roles in setting low-income electricity policy, and discuss three more specific policy areas: universal service, electricity assistance, and health and safety. He discusses the key policy issues that arise when considering these potential federal initiatives and draw upon reviews of proposed low-income policies from restructuring proposals in eight states--California, Massachusetts, New Hampshire, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin.

  3. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    4 Weatherization Population Facts - Roughly 25% of Federally eligible households move in and out of poverty "classification" each year. - The average income of Federally eligible households in FY 2005 was $16,264, based on RECS and Bureau of the Census' Current Population Survey (CPS) data. - States target the neediest, especially the elderly, persons with disabilities, and families with children. - Since the inception of the Weatherization Assistance Program in 1976, over 6.3 million

  4. Household energy use in urban Venezuela: Implications from surveys in Maracaibo, Valencia, Merida, and Barcelona-Puerto La Cruz

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

    This report identifies the most important results of a comparative analysis of household commercial energy use in Venezuelan urban cities. The use of modern fuels is widespread among all cities. Cooking consumes the largest share of urban household energy use. The survey documents no use of biomass and a negligible use of kerosene for cooking. LPG, natural gas, and kerosene are the main fuels available. LPG is the fuel choice of low-income households in all cities except Maracaibo, where 40% of all households use natural gas. Electricity consumption in Venezuela`s urban households is remarkably high compared with the levels used in households in comparable Latin American countries and in households of industrialized nations which confront harsher climatic conditions and, therefore, use electricity for water and space heating. The penetration of appliances in Venezuela`s urban households is very high. The appliances available on the market are inefficient, and there are inefficient patterns of energy use among the population. Climate conditions and the urban built form all play important roles in determining the high level of energy consumption in Venezuelan urban households. It is important to acknowledge the opportunities for introducing energy efficiency and conservation in Venezuela`s residential sector, particularly given current economic and financial constraints, which may hamper the future provision of energy services.

  5. Fact #748: October 8, 2012 Components of Household Expenditures...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Household Expenditures on Transportation, 1984-2010 Fact 748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household ...

  6. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 0.6 0.5 Q 17.4 1 Below 150 percent of poverty line or 60 percent of median State ...

  7. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 1.5 0.5 1.0 14.6 1 Below 150 percent of poverty line or 60 percent of median State ...

  8. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 1.0 3.4 ... weather station. 2 Below 150 percent of poverty line or 60 percent of median State ...

  9. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 0.7 0.4 0.2 18.4 1 Below 150 percent of poverty line or 60 percent of median State ...

  10. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 1.4 2.3 ... were conducted. 2 Below 150 percent of poverty line or 60 percent of median State ...

  11. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 0.9 0.5 0.6 13.0 1 Below 150 percent of poverty line or 60 percent of median State ...

  12. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 1.2 0.7 0.5 11.3 1 Below 150 percent of poverty line or 60 percent of median State ...

  13. Microsoft Word - Household Energy Use CA

    U.S. Energy Information Administration (EIA) Indexed Site

    US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 ... households use 62 million Btu of energy per home, 31% less than the U.S. average. ...

  14. Oregon Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    2012 2013 2014 View History Gross Withdrawals 821 1,407 1,344 770 770 950 1979-2014 From Gas Wells 821 1,407 1,344 770 770 950 1979-2014 From Oil Wells 0 0 0 0 0 0 1996-2014 From ...

  15. New Mexico Natural Gas Gross Withdrawals (Million Cubic Feet...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals (Million Cubic Feet per Day) New Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 4,406...

  16. New York Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) New York Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 149 147...

  17. Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals (Million Cubic Feet per Day) Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 271 275...

  18. US--Federal Offshore Natural Gas Gross Withdrawals (Million Cubic...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet) US--Federal Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  19. West Virginia Natural Gas Gross Withdrawals (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) West Virginia Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006...

  20. Montana Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) Montana Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 317 313...

  1. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    Gasoline and Diesel Fuel Update (EIA)

    Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals (Million Cubic Feet per...

  2. California Natural Gas Gross Withdrawals (Million Cubic Feet...

    Gasoline and Diesel Fuel Update (EIA)

    Gross Withdrawals (Million Cubic Feet per Day) California Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 998...

  3. Kansas Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Gross Withdrawals (Million Cubic Feet per Day) Kansas Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2006 1,049...

  4. Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Arizona Natural Gas Gross Withdrawals (Million Cubic Feet per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct...

  5. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 9.8 2.8 2.1 4.4 0.5 11.6 100 to 150 Percent ...... 5.1 1.4 1.1 2.3 Q 14.2 Above 150 ...

  6. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 15.0 6.7 2.3 ... 4.9 Q Q 0.2 14.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  7. char_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    Income Relative to Poverty Line Below 100 Percent ...... 5.2 3.9 Q Q 1.1 21.9 100 to 150 Percent ...... 6.4 5.2 0.2 Q 0.9 16.5 Above 150 Percent ...

  8. EPA Webinar- Solar for All: Making it Happen in Low-Income Communities

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency (EPA), this webinar is the third in a multi-part series highlighting efforts by state and local agencies, nonprofits, and utilities to bring energy efficiency and renewable energy to low-income households.

  9. Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines and Model Provisions

    Broader source: Energy.gov [DOE]

    The Shared Renewable Energy for Low-to Moderate-Income Consumers: Policy Guidelines and Model Provisions provides information and tools for policymakers, regulators, utilities, shared renewable energy developers, program administrators and others to support the adoption and implementation of shared renewables programs specifically designed to provide tangible benefits to LMI individuals and households.

  10. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No

  11. spaceheat_household2001.pdf

    U.S. Energy Information Administration (EIA) Indexed Site

    1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home

  12. Comparison of energy expenditures by elderly and non-elderly households: 1975 and 1985

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

    The relative position of the elderly in the population is examined and their characteristic use of energy in relation to the total population and their non-elderly counterparts is observed. The 1985 projections are based on demographic, economic, and socio-economic, and energy data assumptions contained in the 1978 Annual Report to Congress. The model used for estimating household energy expenditure is MATH/CHRDS - Micro-Analysis of Transfers to Households/Comprehensive Human Resources Data System. Characteristics used include households disposable income, poverty status, location by DOE region and Standard Metropolitan Statistical Area (SMSA), and race and sex of the household head as well as age. Energy use by fuel type will be identified for total home fuels, including electricity, natural gas, bottled gas and fuel oil, and for all fuels, where gasoline use is also included. Throughout the analysis, both income and expenditure-dollar amounts for 1975 and 1985 are expressed in constant 1978 dollars. Two appendices contain statistical information.

  13. Household energy consumption and expenditures, 1990

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  14. Virginia Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 140,738 147,255 151,094 146,405 139,382 131,885 1967-2014 From Gas Wells 16,046 23,086 20,375 21,802 26,815 27,052 1967-2014 From Oil Wells 0 0 0 9 9 9 2006-2014 From Shale Gas Wells 18,284 16,433 18,501 17,212 13,016 12,226 2007-2014 From Coalbed Wells 106,408 107,736 112,219 107,383 99,542 92,599 2006-2014 Repressuring 0 0 0 0 0 0 2003-2014 Vented and Flared NA NA NA 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 1997-2014

  15. Kansas Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 325,591 309,952 296,299 292,467 286,080 292,450 1967-2015 From Gas Wells 247,651 236,834 264,610 264,223 260,715 1967-2014 From Oil Wells 39,071 37,194 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0 2007-2014 From Coalbed Wells 38,869 35,924 31,689 28,244 25,365 2002-2014 Repressuring 548 521 0 NA NA 1967-2014 Vented and Flared 323 307 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 2002-2014 Marketed Production 324,720 309,124

  16. Pennsylvania Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 572,902 1,310,592 2,256,696 3,259,042 4,214,643 4,768,848 1967-2015 From Gas Wells 173,450 242,305 210,609 207,872 174,576 1967-2014 From Oil Wells 0 0 3,456 2,987 3,564 1967-2014 From Shale Gas Wells 399,452 1,068,288 2,042,632 3,048,182 4,036,504 2007-2014 From Coalbed Wells 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 1967-2014 Vented and Flared 0 0 0 0 0 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 1997-2014 Marketed Production

  17. Kentucky Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 113,300 135,330 124,243 106,122 94,665 78,737 1967-2014 From Gas Wells 111,782 133,521 122,578 106,122 94,665 78,737 1967-2014 From Oil Wells 1,518 1,809 1,665 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 0 2006-2014 Vented and Flared 0 0 0 0 0 0 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 2006-2014 Marketed Production 113,300 135,330 124,243 106,122

  18. Louisiana Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 2,218,283 3,040,523 2,955,437 2,366,943 1,987,630 1,941,727 1967-2015 From Gas Wells 911,967 883,712 775,506 780,623 737,185 1967-2014 From Oil Wells 63,638 68,505 49,380 51,948 50,638 1967-2014 From Shale Gas Wells 1,242,678 2,088,306 2,130,551 1,534,372 1,199,807 2007-2014 From Coalbed Wells 0 0 0 0 0 2002-2014 Repressuring 3,606 5,015 0 2,829 3,199 1967-2014 Vented and Flared 4,578 6,302 0 3,912 4,143 1967-2014 Nonhydrocarbon Gases

  19. Nebraska Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 2,916 2,255 1,980 1,328 1,032 402 1967-2014 From Gas Wells 2,734 2,092 1,854 1,317 1,027 400 1967-2014 From Oil Wells 182 163 126 11 5 1 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0 0 0 0 2006-2014 Repressuring 0 0 0 0 0 0 1967-2014 Vented and Flared 9 24 21 0 NA NA 1967-2014 Nonhydrocarbon Gases Removed 0 0 0 0 0 0 2006-2014 Marketed Production 2,908 2,231 1,959 1,328 1,032 402 1967-2014 Dry Production

  20. ,"West Virginia Natural Gas Gross Withdrawals and Production...

    U.S. Energy Information Administration (EIA) Indexed Site

    Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151991" ,"Release ...

  1. ,"North Dakota Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151989" ,"Release ...

  2. ,"Other States Total Natural Gas Gross Withdrawals and Production...

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ...

  3. ,"U.S. Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Gross Withdrawals and Production",10,"Monthly","22016","1151973" ,"Release ...

  4. Gross Gamma-Ray Calibration Blocks (May 1978) | Department of...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    for, and the Procedures Currently Utilized in, Gross Gamma-Ray Log Calibration (October 1976) Parameter Assignments for Spectral Gamma-Ray Borehole Calibration Models (April 1984

  5. ,"New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Annual",2014 ,"Release...

  6. ,"New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf...

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Annual",2014 ,"Release...

  7. ,"Oregon Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  8. ,"Nevada Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ... Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","1...

  9. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest...

  10. ,"New Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and Production",10,"Annual",2014,"06301967" ,"Release...

  11. Household Response To Dynamic Pricing Of Electricity: A Survey...

    Open Energy Info (EERE)

    Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

  12. Kingston Creek Hydro Project Powers 100 Households | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Kingston Creek Hydro Project Powers 100 Households Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada ...

  13. Energy Information Administration/Household Vehicles Energy Consumptio...

    U.S. Energy Information Administration (EIA) Indexed Site

    , Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related...

  14. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect (OSTI)

    Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

    2009-04-15

    The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

  15. Household energy consumption and expenditures 1993

    SciTech Connect (OSTI)

    1995-10-05

    This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

  16. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  17. Low-income energy assistance programs: a profile of need and policy options

    SciTech Connect (OSTI)

    None

    1980-07-01

    This second report of the Fuel Oil Marketing Advisory Committee (FOMAC) of DOE is twofold: to update information on the energy needs of low-income persons and governmental response to such needs; and to emphasize the need for energy-conservation programs that may alleviate the enormous financial burden placed on low-income people by rising energy prices. FOMAC has continued to develop further and refine its initial energy-conservation recommendations. Mainly, the updated assessment document finds that the poor will expend at least 35% of their income directly on energy and will spend at least 21% of their income on household energy. Other economic impacts of rising energy costs on low-income groups are summarized. Appropriations and stipulations by Congress to aid the lo-income people are reviewed. After careful review of various program designs, FOMAC continues to support the income indexing/vendor line of credit approach. This design provides assistance to elgible households based on: energy needed, cost of fuel, and percentage of income. The cost of implementing the FOMAC design nationally would, according to estimates, range from $3.5 to $4.6 billion for the 1980-1981 winter heating season. A figure of $1.6 to $2.2 billion is being discussed in the Congress. Meeting the ongoing energy needs of the poor will require a coherent national policy which consists of aid in paying energy bills and aid in the poor's effort to conserve energy. The report seeks to promote such policies. Needs assessment, government response, FOMAC model, comments on the programs, projected cost of 1980-1981 Energy Assistance Program, need for conservation programs, and program financing are discussed.

  18. WPN 02-3: 2002 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2002 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  19. WPN 98-5- 1998 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 1998 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  20. WPN 13-3: 2013 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2013 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program (WAP).

  1. WPN 03-3: 2003 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2003 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  2. WPN 04-5: 2004 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2004 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  3. WPN 00-3- 2000 Poverty Income Guidelines and Definition of Income

    Broader source: Energy.gov [DOE]

    To provide states with the 2000 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  4. WPN 07-3: Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2007 poverty income guidelines and definition of income for use in the low-income Weatherization Assistance Program.

  5. WPN 06-5: Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide states with the 2006 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  6. WPN 14-3: 2014 Poverty Income Guidance and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide Grantees with the 2014 Poverty Income Guidelines and Definition of Income for use in the Low-Income Weatherization Assistance Program (WAP).

  7. Kentucky Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Kentucky Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  8. Maryland Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Maryland Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  9. Nebraska Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells Nebraska Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  10. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect (OSTI)

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  11. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov ...

  12. Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals...

    U.S. Energy Information Administration (EIA) Indexed Site

    Oil Wells (Million Cubic Feet) Federal Offshore--Gulf of Mexico Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov ...

  13. Physics Nobel winner David Gross gives public lecture at Jefferson...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Physics Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) ... "The Coming Revolutions in Fundamental Physics" beginning at 8 p.m. at Jefferson Lab on ...

  14. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Oil Wells (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  15. Montana Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Montana Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 4,561 3,826 4,106 ...

  16. Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 7,051 6,368 ...

  17. Louisiana Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 425,704 369,500 ...

  18. Florida Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Florida Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1996 - - - - - - - - - ...

  19. Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1 1 1 1 1 1 1 1 1 1 ...

  20. California Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) California Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 13,569 12,155 ...

  1. California Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 10,998 9,933 ...

  2. Michigan Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Michigan Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 9,579 8,593 ...

  3. Texas Natural Gas Gross Withdrawals from Gas Wells (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Texas Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 507,274 440,015 ...

  4. Oklahoma Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Oklahoma Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 163,978 147,543 ...

  5. Montana Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Montana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1,239 1,119 1,239 ...

  6. Michigan Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Michigan Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 11,582 10,461 ...

  7. Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 1,273 1,150 ...

  8. Oregon Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Gas Wells (Million Cubic Feet) Oregon Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 246 244 232 ...

  9. Colorado Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 11,749 10,612 ...

  10. Mississippi Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Mississippi Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 14,797 13,076 ...

  11. Colorado Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (Million Cubic Feet) Colorado Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 15,390 18,697 ...

  12. Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Shale Gas (Million Cubic Feet) Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 ...

  13. Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic...

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 107,415 97,020 ...

  14. Nevada Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    from Gas Wells (Million Cubic Feet) Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8...

  15. Fact #564: March 30, 2009 Transportation and the Gross Domestic...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Housing, health care, and food are the only categories with greater shares of the GDP. GDP ... Gross Domestic Product, 2007 Housing 24.3% Health Care 17.4% Food 11.6% ...

  16. Fact# 904: December 21, 2015 Gross Domestic Product and Vehicle...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    With the growth of VMT in 2015, the gap between the two series has narrowed for the first time since the Great Recession. GDP and VMT Trends, 1960-2015 Graph showing gross national ...

  17. Property:CoolingTowerWaterUseSummerGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name CoolingTowerWaterUseSummerGross Property Type Number Description Cooling Tower Water use (summer average) (afday) Gross. Retrieved from "http:en.openei.orgw...

  18. ,"U.S. Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)" "Sourcekey","NGMEPG0FGSNUSMMCF" "Date","U.S. Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)" ...

  19. Messaging Strategies for Low-Income Participants

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program, BetterBuildings Low-Income Peer Exchange Call: Messaging and Messaging Strategies for Low-Income Program Participants, May 12, 2011.

  20. WPN 15-3: 2015 Poverty Income Guidelines and Definition of Income |

    Energy Savers [EERE]

    Department of Energy 3: 2015 Poverty Income Guidelines and Definition of Income WPN 15-3: 2015 Poverty Income Guidelines and Definition of Income Archived 02/10/16, Superseded by WPN 16-3 To provide Grantees with the 2015 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program (WAP). PDF icon WPN 15-3: 2015 Poverty Income Guidelines and Definition of Income More Documents & Publications WPN 14-3: 2014 Poverty Income Guidance and

  1. Gross alpha analytical modifications that improve wastewater treatment compliance

    SciTech Connect (OSTI)

    Tucker, B.J.; Arndt, S.

    2007-07-01

    This paper will propose an improvement to the gross alpha measurement that will provide more accurate gross alpha determinations and thus allow for more efficient and cost-effective treatment of site wastewaters. To evaluate the influence of salts that may be present in wastewater samples from a potentially broad range of environmental conditions, two types of efficiency curves were developed, each using a thorium-230 (Th-230) standard spike. Two different aqueous salt solutions were evaluated, one using sodium chloride, and one using salts from tap water drawn from the Bergen County, New Jersey Publicly Owned Treatment Works (POTW). For each curve, 13 to 17 solutions were prepared, each with the same concentration of Th-230 spike, but differing in the total amount of salt in the range of 0 to 100 mg. The attenuation coefficients were evaluated for the two salt types by plotting the natural log of the counted efficiencies vs. the weight of the sample's dried residue retained on the planchet. The results show that the range of the slopes for each of the attenuation curves varied by approximately a factor of 2.5. In order to better ensure the accuracy of results, and thus verify compliance with the gross alpha wastewater effluent criterion, projects depending on gross alpha measurements of environmental waters and wastewaters should employ gross alpha efficiency curves prepared with salts that mimic, as closely as possible, the salt content of the aqueous environmental matrix. (authors)

  2. Determinants of Household Use of Selected Energy Star Appliances - Energy

    U.S. Energy Information Administration (EIA) Indexed Site

    Information Administration Determinants of Household Use of Selected Energy Star Appliances Release date: May 25, 2016 Introduction According to the 2009 Residential Energy Consumption Survey (RECS), household appliances1accounted for 35% of U.S. household energy consumption, up from 24% in 1993. Thus, improvements in the energy performance of residential appliances as well as increases in the use of more efficient appliances can be effective in reducing household energy consumption and

  3. Strategies for Collecting Household Energy Data | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012. PDF icon Call Slides and Discussion Summary More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  4. Low-Income Weatherization: The Human Dimension

    Broader source: Energy.gov [DOE]

    This presentation focuses on how the human dimension saves energy within low-income weatherization programs.

  5. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  6. Household energy consumption and expenditures, 1987

    SciTech Connect (OSTI)

    Not Available

    1989-10-10

    Household Energy Consumption and Expenditures 1987, Part 1: National Data is the second publication in a series from the 1987 Residential Energy Consumption Survey (RECS). It is prepared by the Energy End Use Division (EEUD) of the Office of Energy Markets and End Use (EMEU), Energy Information Administration (EIA). The EIA collects and publishes comprehensive data on energy consumption in occupied housing units in the residential sector through the RECS. 15 figs., 50 tabs.

  7. Left to Our Own Devices – Financing Efficiency for Small Business and Low-Income Families (2009 Environmental Defense Fund Report)

    Broader source: Energy.gov [DOE]

    There is a widely known gap between cost-effective behavior, consumption patterns and actual marketplace conditions. This engineering gap/efficiency gap is particularly the case for low-income households and small businesses, which tend to depend on older, inefficient equipment. This study identifies the limitations of current and potential of relatively new mechanisms for efficiency investment micro-financing.

  8. Household and environmental characteristics related to household energy-consumption change: A human ecological approach

    SciTech Connect (OSTI)

    Guerin, D.A.

    1988-01-01

    This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = <.05) relationship between the dependent-variable energy-consumption change and the predictor variables heating degree days, addition of insulation, addition of a wood-burning stove, year the housing unit was built, and weighted number of appliances. A significant (p = <.05) relationship was found between the criterion variable energy-consumption change and the discriminating variables of age of the head of the household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

  9. Other States Natural Gas Gross Withdrawals from Gas Wells (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Other States Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 72,328 63,451 67,732 63,118 62,276 59,557 ...

  10. New Mexico Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 1,341,475 1,287,682 1,276,296 1,247,394 1,265,579 1,289,908 1967-2015 From Gas Wells 616,134 556,024 653,057 588,127 ...

  11. Federal Offshore Louisiana Natural Gas Gross Withdrawals and...

    U.S. Energy Information Administration (EIA) Indexed Site

    Data Series Area 2009 2010 2011 2012 2013 2014 View History Gross Withdrawals NA NA NA 0 0 0 1977-2014 From Gas Wells NA NA NA 0 0 0 1977-2014 From Oil Wells NA NA NA 0 0 0 ...

  12. Kansas Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 0 0 0 0 ...

  13. Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 ...

  14. Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million...

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 0 0 0 0 0 0 0 0 0 0 0 0 2008 0 0 0 0 0 0 0 0 0 0 0 0 ...

  15. Messaging Strategies for Low-Income Participants | Department...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Messaging Strategies for Low-Income Participants Messaging Strategies for Low-Income Participants Better Buildings Neighborhood Program, BetterBuildings Low-Income Peer Exchange ...

  16. Property:CoolingTowerWaterUseAnnlAvgGross | Open Energy Information

    Open Energy Info (EERE)

    Property Name CoolingTowerWaterUseAnnlAvgGross Property Type Number Description Cooling Tower Water use (annual average) (afday) Gross. Retrieved from "http:en.openei.orgw...

  17. Property:CoolingTowerWaterUseWinterGross | Open Energy Information

    Open Energy Info (EERE)

    lingTowerWaterUseWinterGross Property Type Number Description Cooling Tower Water use (winter average) (afday) Gross. Retrieved from "http:en.openei.orgwindex.php?titleProper...

  18. Louisiana Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Louisiana Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,838,521 4,600,197 4,750,119 1980's 4,617,585 4,584,491 4,246,464 3,635,942 4,070,279 3,542,827 3,279,165 3,610,041 3,633,594 3,577,685 1990's 3,731,764 3,550,230 3,442,437 3,508,112 3,673,494 3,554,147 3,881,697 3,941,802 3,951,997 3,896,569 2000's 3,812,991 153,871 137,192 133,456

  19. Louisiana--State Offshore Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals (Million Cubic Feet) Louisiana--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 498,876 487,512 1980's 417,312 381,938 366,546 322,588 319,638 256,736 207,265 225,599 214,645 204,005 1990's 182,240 148,429 138,101 157,011 159,513 94,044 192,527 180,848 192,956 164,523 2000's 141,567 153,871 137,192 133,456 129,245 107,584 97,479 72,868 86,198 76,386 2010's 69,836

  20. Louisiana--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Louisiana--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 1,535,033 1,538,511 1,552,603 1,608,633 1,469,698 1,357,155 1,386,478 1,434,389 2000's 1,342,963 1,370,802 1,245,270 1,244,672 1,248,050 1,202,328 1,280,758 1,309,960 1,301,523 1,482,252 2010's 2,148,447 2,969,297 2,882,193 2,289,193 1,925,968 - = No Data Reported; -- = Not Applicable; NA = Not Available;

  1. Alabama Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Alabama Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 0 9 13 1990's 19,861 32,603 191,605 218,023 349,380 356,598 361,068 409,091 392,320 376,435 2000's 361,289 200,862 202,002 194,339 165,630 152,902 145,762 134,451 125,502 109,214 2010's 101,487 84,270 87,398 75,660 70,827 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  2. Alabama--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alabama--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 222,009 228,298 229,483 223,527 221,233 220,674 212,470 207,863 2000's 200,255 191,119 184,500 176,571 173,106 164,304 160,381 155,167 152,051 146,751 2010's 139,215 134,305 128,312 120,666 110,226 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  3. Alaska Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals Total Offshore (Million Cubic Feet) Alaska Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 72,813 71,946 1980's 63,355 71,477 66,852 68,776 68,315 62,454 63,007 69,656 101,440 122,595 1990's 144,064 171,665 216,377 233,198 224,301 113,552 126,051 123,854 133,111 125,841 2000's 263,958 262,937 293,580 322,010 334,125 380,568 354,816 374,204 388,188 357,490 2010's 370,148 364,702

  4. Alaska--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alaska--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,409,336 2,545,144 2,861,599 3,256,352 3,247,533 3,257,096 3,245,736 3,236,241 2000's 3,265,436 3,164,843 3,183,857 3,256,295 3,309,960 3,262,379 2,850,934 3,105,086 3,027,696 2,954,896 2010's 2,826,952 2,798,220 2,857,485 2,882,956 2,803,429 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  5. Calif--onshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Calif--onshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 386,382 346,733 334,987 322,544 326,919 317,137 315,701 347,667 2000's 334,983 336,629 322,138 303,480 287,205 291,271 301,921 286,584 281,088 258,983 2010's 273,136 237,388 214,509 219,386 218,512 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. California Natural Gas Gross Withdrawals Total Offshore (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals Total Offshore (Million Cubic Feet) California Natural Gas Gross Withdrawals Total Offshore (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5,417 19,929 20,394 1980's 19,980 26,692 31,904 38,084 60,207 84,062 77,355 67,835 60,308 59,889 1990's 58,055 59,465 62,473 58,635 60,765 60,694 73,092 80,516 81,868 84,547 2000's 83,882 78,209 74,884 64,961 61,622 60,773 47,217 52,805 51,931 47,281 2010's 46,755 41,742

  7. Federal Offshore California Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals (Million Cubic Feet) Federal Offshore California Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 5,417 5,166 5,431 1980's 5,900 12,763 17,751 24,168 46,363 64,558 59,078 54,805 49,167 50,791 1990's 49,972 51,855 55,231 52,150 53,561 54,790 66,784 73,345 74,985 77,809 2000's 76,075 70,947 67,816 58,095 54,655 54,088 40,407 45,516 44,902 41,229 2010's 41,200 36,579 27,262 27,454

  8. Federal Offshore--Alabama Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Offshore--Alabama Natural Gas Gross Withdrawals (Million Cubic Feet) Federal Offshore--Alabama Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 0 0 0 1990's 0 0 79,294 86,515 120,502 143,703 152,055 194,677 170,320 163,763 2000's 160,208 NA NA NA NA NA NA NA NA NA 2010's NA NA 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  9. Federal Offshore--Louisiana Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals (Million Cubic Feet) Federal Offshore--Louisiana Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 3,838,521 4,101,321 4,262,607 1980's 4,200,273 4,202,553 3,879,918 3,313,354 3,750,641 3,286,091 3,071,900 3,384,442 3,418,949 3,373,680 1990's 3,549,524 3,401,801 3,304,336 3,351,101 3,513,981 3,460,103 3,689,170 3,760,953 3,759,040 3,732,046 2000's 3,671,424 NA NA NA NA NA NA NA NA NA

  10. Household energy consumption and expenditures 1987

    SciTech Connect (OSTI)

    Not Available

    1990-01-22

    This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

  11. Barriers to household investment in residential energy conservation: preliminary assessment

    SciTech Connect (OSTI)

    Hoffman, W.L.

    1982-12-01

    A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

  12. Household energy consumption and expenditures, 1990. [Contains Glossary

    SciTech Connect (OSTI)

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  13. WPN 05-4a- 2005 Poverty Income Guidelines and Definition of Income to Exclude Combat Zone Pay

    Broader source: Energy.gov [DOE]

    To provide states with the 2005 Poverty Income Guidelines and Definition of Income for use in the low-income Weatherization Assistance Program.

  14. An Analysis of the Price Elasticity of Demand for Household Appliances

    SciTech Connect (OSTI)

    Fujita, Kimberly; Dale, Larry; Fujita, K. Sydny

    2008-01-25

    This report summarizes our study of the price elasticity of demand for home appliances, including refrigerators, clothes washers, and dishwashers. In the context of increasingly stringent appliance standards, we are interested in what kind of impact the increased manufacturing costs caused by higher efficiency requirements will have on appliance sales. We begin with a review of existing economics literature describing the impact of economic variables on the sale of durable goods.We then describe the market for home appliances and changes in this market over the past 20 years, performing regression analysis on the shipments of home appliances and relevant economic variables including changes to operating cost and household income. Based on our analysis, we conclude that the demand for home appliances is price inelastic.

  15. Physics Nobel winner David Gross gives public lecture at Jefferson Lab on

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    June 12 (Monday) | Jefferson Lab Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) Physics Nobel winner David Gross gives public lecture at Jefferson Lab on June 12 (Monday) June 6, 2006 David Gross David Gross, Nobel Prize recipient and lecturer David Gross, Nobel Prize recipient is scheduled to give a free, public lecture titled "The Coming Revolutions in Fundamental Physics" beginning at 8 p.m. at Jefferson Lab on (Monday) June 12. He is one of

  16. California--State Offshore Natural Gas Gross Withdrawals (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Gross Withdrawals (Million Cubic Feet) California--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 14,763 14,963 1980's 14,080 13,929 14,153 13,916 13,844 19,504 18,277 13,030 11,141 9,098 1990's 8,083 7,610 7,242 6,484 7,204 5,904 6,309 7,171 6,883 6,738 2000's 7,808 7,262 7,068 6,866 6,966 6,685 6,809 7,289 7,029 6,052 2010's 5,554 5,163 5,051 5,470 5,961 - = No Data Reported; -- =

  17. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    per Household and Other Demographic Statistics Fact 618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per ...

  18. Low Income Home Energy Assistance Program (LIHEAP)

    Broader source: Energy.gov [DOE]

    The Low Income Home Energy Assistance Program (LIHEAP) provides resources to assist families with energy costs. This federally funded assistance helps in managing costs associated with:

  19. Low Income Energy Efficiency Workgroup Meeting #1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    for a session at the Efficiency Exchange conference in April and is looking for winning strategies for acquiring low income energy efficiency. The first session focused on...

  20. Reconstructing householder vectors from Tall-Skinny QR

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstratemore » the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.« less

  1. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect (OSTI)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstrate the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.

  2. WPN 12-8: 2012 Poverty Income Guidelines and Definition of Income

    Office of Energy Efficiency and Renewable Energy (EERE)

    To provide Grantees with the 2012 Poverty Income Guidelines and Definition of Income for use in the U.S. Department of Energy’s (DOE) Weatherization Assistance Program (WAP).

  3. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    9 2005 Housing Unit Ownership, by Income Level and Weatherization Eligibility (Millions) Single-Family Multi-Family Unit Mobile Home 2005 Household Income Own Rent Own Rent Own Rent Less than $15,000 6.1 2.4 0.3 7.1 1.6 N.A. $15,000 to $30,000 11.0 3.0 0.4 5.8 2.2 0.3 $30,000 to $49,999 15.7 2.5 N.A 3.9 1.2 N.A. All Households 68.2 10.7 4.2 20.1 5.7 1.0 Federally Eligible 10.9 4.5 1.1 9.4 2.5 0.6 Federally Ineligible 57.3 6.2 3.1 10.7 3.2 0.4 Below 100% Poverty Line 5.3 2.4 0.7 6.1 1.5 0.3

  4. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  5. Measuring Income and Projecting Energy Use

    SciTech Connect (OSTI)

    Pitcher, Hugh M.

    2009-11-01

    Abstract: Energy is a key requirement for a healthy, productive life and a major driver of the emissions leading to an increasingly warm planet. The implications of a doubling and redoubling of per capita incomes over the remainder of this century for energy use are a critical input into understanding the magnitude of the carbon management problem. A substantial controversy about how the Special Report on Emssions Scenarios (SRES) measured income and the potential implications of how income was measured for long term levels of energy use is revisited again in the McKibbin, Pearce and Stegman article appearing elsewhere in this issue. The recent release of a new set of purchasing power estimates of national income, and the preparations for creating new scenarios to support the IPCCs fifth assessment highlight the importance of the issues which have arisen surrounding income and energy use. Comparing the 1993 and 2005 ICP results on Purchasing Power Parity (PPP) based measures of income reveals that not only do the 2005 ICP estimates share the same issue of common growth rates for real income as measured by PPP and US $, but the lack of coherence in the estimates of PPP incomes, especially for developing countries raises yet another obstacle to resolving the best way to measure income. Further, the common use of an income term to mediate energy demand (as in the Kaya identity) obscures an underlying reality about per capita energy demands, leading to unreasonable estimates of the impact of changing income measures and of the recent high GDP growth rates in India and China. Significant new research is required to create both a reasonable set of GDP growth rates and long term levels of energy use.

  6. Table 6.4 Natural Gas Gross Withdrawals and Natural Gas Well Productivity, 1960-2011

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals and Natural Gas Well Productivity, 1960-2011 Year Natural Gas Gross Withdrawals From Crude Oil, Natural Gas, Coalbed, and Shale Gas Wells Natural Gas Well Productivity Texas 1 Louisiana 1 Oklahoma Other States 1 Federal Gulf of Mexico 2 Total Onshore Offshore Total Gross With- drawals From Natural Gas Wells 3 Producing Wells 4 Average Productivity Federal State Total Million Cubic Feet Million Cubic Feet Million Cubic Feet Number Cubic Feet per Well 1960 6,964,900

  7. Table 2. Percent of Households with Vehicles, Selected Survey...

    U.S. Energy Information Administration (EIA) Indexed Site

    Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08...

  8. Fact #614: March 15, 2010 Average Age of Household Vehicles

    Broader source: Energy.gov [DOE]

    The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first...

  9. Household heating bills expected to be lower this winter

    U.S. Energy Information Administration (EIA) Indexed Site

    In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating ...

  10. Virginia Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 19,038 37,808 41,230 2000's 36,700 33,118 34,936 35,256 48,784 66,951 60,321 90,573 76,983 94,829 2010's 139,755 142,284 189,848 171,588 158,672 243,116

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 140,738 147,255 151,094 146,405 139,382 131,885 1967-2014 From Gas Wells 16,046 23,086 20,375 21,802 26,815 27,052 1967-2014 From Oil Wells 0 0 0 9 9 9 2006-2014 From Shale Gas Wells 18,284

  11. Other States Total Natural Gas Gross Withdrawals and Production

    U.S. Energy Information Administration (EIA) Indexed Site

    Monthly-Million Cubic Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History Gross Withdrawals 5,864,402 6,958,125 8,225,321 689,082 633,853 596,357 1991-2015 From Gas Wells 2,523,173 2,599,172 3,177,021 362,605 328,809 1991-2014 From Oil Wells 691,643 728,857 279,627 23,391 22,817 1991-2014 From

  12. Oregon Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 24,171 52,846 49,661 2000's 69,451 82,542 55,854 74,400 88,734 87,998 75,186 101,503 116,637 108,705 2010's 108,827 60,252 81,444 101,930 90,099 113,988

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 821 1,407 1,344 770 770 950 1979-2014 From Gas Wells 821 1,407 1,344 770 770 950 1979-2014 From Oil Wells 0 0 0 0 0 0 1996-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0

  13. Pennsylvania Natural Gas Gross Withdrawals from Coalbed Wells (Million

    Gasoline and Diesel Fuel Update (EIA)

    Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 20,430 30,240 31,353 2000's 20,597 22,632 50,251 41,238 76,186 80,640 100,946 143,954 141,011 210,542 2010's 245,559 306,266 393,775 362,349 390,816 439,248

    10 2011 2012 2013 2014 2015 View History Gross Withdrawals 572,902 1,310,592 2,256,696 3,259,042 4,214,643 4,768,848 1967-2015 From Gas Wells 173,450 242,305 210,609 207,872 174,576 1967-2014 From Oil Wells 0 0 3,456 2,987 3,564 1967-2014

  14. Gross national happiness as a framework for health impact assessment

    SciTech Connect (OSTI)

    Pennock, Michael; Ura, Karma

    2011-01-15

    The incorporation of population health concepts and health determinants into Health Impact Assessments has created a number of challenges. The need for intersectoral collaboration has increased; the meaning of 'health' has become less clear; and the distinctions between health impacts, environmental impacts, social impacts and economic impacts have become increasingly blurred. The Bhutanese concept of Gross National Happiness may address these issues by providing an over-arching evidence-based framework which incorporates health, social, environmental and economic contributors as well as a number of other key contributors to wellbeing such as culture and governance. It has the potential to foster intersectoral collaboration by incorporating a more limited definition of health which places the health sector as one of a number of contributors to wellbeing. It also allows for the examination of the opportunity costs of health investments on wellbeing, is consistent with whole-of-government approaches to public policy and emerging models of social progress.

  15. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim; Schmoyer, Richard L; Chin, Shih-Miao

    2007-05-01

    Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

  16. Determinants of Household Use of Selected Energy Star Appliances

    U.S. Energy Information Administration (EIA) Indexed Site

    Determinants of Household Use of Selected Energy Star Appliances May 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Determinants of Household Use of Selected Energy Star Appliances i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of

  17. Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray

    Energy Savers [EERE]

    Logging Systems (December 1983) | Department of Energy Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) PDF icon Grade Assignments for Models Used for Calibration of Gross-Count Gamma-Ray Logging Systems (December 1983) More

  18. Spatial confinement and thermal deconfinement in the Gross-Neveu model

    SciTech Connect (OSTI)

    Malbouisson, J. M. C.; Khanna, F. C.; Malbouisson, A. P. C.

    2007-06-19

    We discuss the occurrence of spatial confinement and thermal deconfinement in the massive, D-dimensional, Gross-Neveu model with compactified spatial dimensions.

  19. Shared Renewable Energy for Low-to-Moderate Income Consumers...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines and Model Provisions Shared Renewable Energy for Low-to-Moderate Income Consumers: Policy Guidelines ...

  20. Better Buildings Neighborhood Program Multi-family and Low Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Multi- family and Low Income Peer Exchange Call: Working with Condominium Owners and ... Buildings (17%) * Working with Middle Income Multifamily Buildings (50%) Participants ...

  1. Better Buildings Program San Jose -- Serving Moderate Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Program San Jose -- Serving Moderate Income Residents Better Buildings Program San Jose -- Serving Moderate Income Residents Provides an overview of the program components and ...

  2. Effective Energy Behavior Change for Low-Income Weatherization...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Effective Energy Behavior Change for Low-Income Weatherization Clients Effective Energy Behavior Change for Low-Income Weatherization Clients This document contains the transcript ...

  3. Better Buildings Low Income Peer Exchange CallFeaturing: Case...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    BetterBuildings Low Income Peer Exchange Call Featuring: Case study on integration of ... and Roll Call * Case study on integration of income-qualified programs into ...

  4. LIEE (LOW-INCOME ENERGY EFFICIENCY) GRANT PROGRAM VERSUS THE...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    614 LIEE (LOW-INCOME ENERGY EFFICIENCY) GRANT PROGRAM VERSUS THE UTILITY LOW-INCOME WEATHERIZATION & DUCT SEALING PROGRAM Program Requirements and Specifications Grant Program-...

  5. Proposed Structure and Organizing Principles for Low Income Energy...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Structure and Organizing Principles for Low Income Energy Efficiency Workgroup 1 Background As part of Post-2011-Review, BPA agreed to convene a low income energy efficiency...

  6. Other States Natural Gas Gross Withdrawals from Coalbed Wells (Million

    U.S. Energy Information Administration (EIA) Indexed Site

    Cubic Feet) Coalbed Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2002 0 0 0 0 0 0 0 0 0 0 0 0 2003 5,335 4,954 5,465 5,228 5,405 5,163 4,817 5,652 5,165 5,347 4,814 5,420 2004 5,684 5,278 5,822 5,570 5,758 5,500 5,132 6,022 5,502 5,697 5,129 5,774 2005 5,889 5,469 6,033 5,771 5,967 5,699 5,318 6,240 5,702 5,903 5,315 5,983 2006 16,225 14,883 16,627 15,979 16,802 16,447 16,891

  7. Kentucky Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,194 5,782 5,686 2000's 4,202 4,433 13,712 3,667 4,833 17,181 12,287 19,376 9,584 8,399 2010's 19,284 15,575 31,194 14,536 26,919 52,015

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 113,300 135,330 124,243 106,122 94,665 78,737 1967-2014 From Gas Wells 111,782 133,521 122,578 106,122 94,665 78,737 1967-2014 From Oil Wells 1,518 1,809 1,665 0 0 0 1967-2014 From Shale Gas Wells 0 0 0 0 0

  8. Nebraska Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    Gasoline and Diesel Fuel Update (EIA)

    Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 2,687 5,080 4,582 2000's 5,522 4,290 4,947 4,593 3,340 8,066 7,787 10,908 7,230 3,331 2010's 3,949 4,223 7,696 5,080 4,132 4,634

    09 2010 2011 2012 2013 2014 View History Gross Withdrawals 2,916 2,255 1,980 1,328 1,032 402 1967-2014 From Gas Wells 2,734 2,092 1,854 1,317 1,027 400 1967-2014 From Oil Wells 182 163 126 11 5 1 1967-2014 From Shale Gas Wells 0 0 0 0 0 0 2007-2014 From Coalbed Wells 0 0 0

  9. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  10. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  11. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-22

    Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide‐range social marketing activities to promote energy conservation.

  12. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New York MPOs. The 1995 and 2001 survey data make it possible to examine and identify travel trends over time. This report does not address, however, the causes of the differences and/or trends.

  13. New York Natural Gas Gross Withdrawals from Coalbed Wells (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Coalbed Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Coalbed Wells New York Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Coalbed

  14. Oregon Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Shale Gas Wells Oregon Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Shale Gas

  15. Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    from Oil Wells (Million Cubic Feet) Missouri Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 NA NA 2010's NA NA NA 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Oil Wells Missouri Natural Gas Gross Withdrawals

  16. Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    from Gas Wells (Million Cubic Feet) Nevada Natural Gas Gross Withdrawals from Gas Wells (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 0 2010's 0 0 0 0 3 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Gas Wells Nevada Natural Gas Gross Withdrawals and

  17. Nevada Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 0 0 0 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 4/29/2016 Next Release Date: 5/31/2016 Referring Pages: Natural Gas Gross Withdrawals from Shale Gas Wells Nevada Natural Gas Gross Withdrawals and Production Natural Gas Gross Withdrawals from Shale

  18. Household Vehicles Energy Use: Latest Data and Trends - Table...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    ... 6.5 1.5 15.4 957 1,031 Income Relative to Poverty Line Below 100 Percent... 7.9 1.4 14.7 942 937...

  19. Fact #564: March 30, 2009 Transportation and the Gross Domestic Product, 2007

    Broader source: Energy.gov [DOE]

    Transportation plays a major role in the U.S. economy. About 10% of the U.S. Gross Domestic Product (GDP) in 2007 is related to transportation. Housing, health care, and food are the only...

  20. EIA Energy Efficiency-Table 4e. Gross Output by Selected Industries...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    e Page Last Modified: May 2010 Table 4e. Gross Output1by Selected Industries, 1998, 2002, and 2006 (Billion 2000 Dollars 2) MECS Survey Years NAICS Subsector and Industry 1998 2002...

  1. EIA Energy Efficiency-Table 3e. Gross Output by Selected Industries...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    e Page Last Modified: May 2010 Table 3e. Gross Output1 by Selected Industries, 1998, 2002, and 2006 (Current Billion Dollars) MECS Survey Years NAICS Subsector and Industry 1998...

  2. Fact #621: May 3, 2010 Gross Vehicle Weight vs. Empty Vehicle Weight

    Office of Energy Efficiency and Renewable Energy (EERE)

    The gross weight of a vehicle (GVW) is the weight of the empty vehicle plus the weight of the maximum payload that the vehicle was designed to carry. In cars and small light trucks, the difference...

  3. The one-dimensional Gross-Pitaevskii equation and its some excitation states

    SciTech Connect (OSTI)

    Prayitno, T. B.

    2015-04-16

    We have derived some excitation states of the one-dimensional Gross-Pitaevskii equation coupled by the gravitational potential. The methods that we have used here are taken by pursuing the recent work of Kivshar et. al. by considering the equation as a macroscopic quantum oscillator. To obtain the states, we have made the appropriate transformation to reduce the three-dimensional Gross-Pitaevskii equation into the one-dimensional Gross-Pitaevskii equation and applying the time-independent perturbation theory in the general solution of the one-dimensional Gross-Pitaevskii equation as a linear superposition of the normalized eigenfunctions of the Schrödinger equation for the harmonic oscillator potential. Moreover, we also impose the condition by assuming that some terms in the equation should be so small in order to preserve the use of the perturbation method.

  4. 23 V.S.A. Section 1392 Gross Weight Limits on Highways | Open...

    Open Energy Info (EERE)

    Section 1392 Gross Weight Limits on HighwaysLegal Abstract Statute establishes the motor vehicle weight, load size, not to exceed 80,000 pounds without a permit. Published NA...

  5. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Kingston Creek Hydro Project Powers 100 Households EERE Success Story-Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting ...

  6. Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles

    Broader source: Energy.gov [DOE]

    Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of...

  7. Fact #747: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure

    Broader source: Energy.gov [DOE]

    Except for housing, transportation was the largest single expenditure for the average American household in 2010. The average household spends more on transportation in a year than on food. Vehicle...

  8. Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles

    Broader source: Energy.gov [DOE]

    When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles...

  9. Heating oil and propane households bills to be lower this winter...

    U.S. Energy Information Administration (EIA) Indexed Site

    Heating oil and propane households bills to be lower this winter despite recent cold spell Despite the recent cold weather, households that use heating oil or propane as their main ...

  10. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic Statistics

    Broader source: Energy.gov [DOE]

    Since 1969, the number of vehicles per household has increased by 66% and the number of vehicles per licensed driver has increased by 47%. The number of workers per household has changed the least...

  11. EmPOWER Maryland Low Income Energy Efficiency Program

    Broader source: Energy.gov [DOE]

    The Maryland Department of Housing and Community Development (DHCD) EmPOWER Maryland Low Income Energy Efficiency Program helps qualifying low-income residents increase the energy efficiency of t...

  12. Household Vehicles Energy Use: Latest Data and Trends - Table...

    Gasoline and Diesel Fuel Update (EIA)

    ... 9.6 5.0 100 4.4 6.2 4.5 0.8 6.8 4.5 Income Relative to Poverty Line Below 100 Percent... 11.4 6.0 116 5.1 5.6...

  13. ,"Texas--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1060_rtxsf_2a.xls"

  14. ,"US--Federal Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Federal Offshore Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","US--Federal Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  15. ,"US--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    State Offshore Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","US--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  16. ,"Alabama--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1060_ralsf_2a.xls"

  17. ,"Alaska--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1060_raksf_2a.xls"

  18. ,"California--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  19. ,"Federal Offshore California Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore California Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  20. ,"Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gulf of Mexico Natural Gas Gross Withdrawals and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore Gulf of Mexico Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1997" ,"Release Date:","4/29/2016" ,"Next Release

  1. ,"Federal Offshore--Alabama Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Alabama Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  2. ,"Federal Offshore--Louisiana Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Louisiana Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  3. ,"Federal Offshore--Texas Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Natural Gas Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Federal Offshore--Texas Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  4. ,"Louisiana--State Offshore Natural Gas Gross Withdrawals (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana--State Offshore Natural Gas Gross Withdrawals (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  5. Gross error detection and stage efficiency estimation in a separation process

    SciTech Connect (OSTI)

    Serth, R.W.; Srikanth, B. . Dept. of Chemical and Natural Gas Engineering); Maronga, S.J. . Dept. of Chemical and Process Engineering)

    1993-10-01

    Accurate process models are required for optimization and control in chemical plants and petroleum refineries. These models involve various equipment parameters, such as stage efficiencies in distillation columns, the values of which must be determined by fitting the models to process data. Since the data contain random and systematic measurement errors, some of which may be large (gross errors), they must be reconciled to obtain reliable estimates of equipment parameters. The problem thus involves parameter estimation coupled with gross error detection and data reconciliation. MacDonald and Howat (1988) studied the above problem for a single-stage flash distillation process. Their analysis was based on the definition of stage efficiency due to Hausen, which has some significant disadvantages in this context, as discussed below. In addition, they considered only data sets which contained no gross errors. The purpose of this article is to extend the above work by considering alternative definitions of state efficiency and efficiency estimation in the presence of gross errors.

  6. "Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual"

    U.S. Energy Information Administration (EIA) Indexed Site

    Real Gross Domestic Product Growth Trends, Projected vs. Actual" "Projected Real GDP Growth Trend" " (cumulative average percent growth in projected real GDP from first year shown for each AEO)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO

  7. Households to pay more than expected to stay warm this winter

    U.S. Energy Information Administration (EIA) Indexed Site

    November, U.S. households are forecast to consume more heating fuels than ... That's the latest forecast from the U.S. Energy Information Administration. Propane users ...

  8. Household Vehicles Energy Use: Latest Data and Trends - Table...

    Annual Energy Outlook [U.S. Energy Information Administration (EIA)]

    11.5 0.8 1.0 0.9 0.8 0.7 0.8 0.7 1.6 1.4 0.8 0.5 0.2 0.1 0.7 0.4 Income Relative to Poverty Line Below 100 Percent... 13.3 0.3 0.4 0.4 0.6...

  9. Effective Energy Behavior Change for Low-Income Weatherization Clients

    Broader source: Energy.gov [DOE]

    This document contains the transcript for the Effective Energy Behavior Change for Low-Income Weatherization Clients webinar presented on May 31, 2012.

  10. Better Buildings Residential Network Multifamily & Low-Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... call series distribution lists to peerexchange@rossstrategic.com 6 Data & Evaluation Financing & Revenue Marketing & Outreach Multifamily Low-Income Housing ...

  11. Better Buildings Residential Multifamily/Low-Income Peer Exchange...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... series distribution lists to peerexchange@rossstrategic.com. 6 Data & Evaluation Financing & Revenue Marketing & Outreach Multi-Family Low Income Housing ...

  12. Better Buildings Residential Network Multi-Family/ Low Income...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... INHP decided to find the expertise * Strong partner with a local utility * Contracted ... housing for: * low and moderate income families, * the elderly, * individuals with ...

  13. Approaches to Electric Utility Energy Efficiency for Low Income...

    Open Energy Info (EERE)

    Approaches to Electric Utility Energy Efficiency for Low Income Customers in a Changing Regulatory Environment Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Approaches...

  14. The Denver Energy Challenge-- Serving Moderate Income Residents

    Broader source: Energy.gov [DOE]

    Provides an overview of the Denver Energy Challenge and how services were expanded to moderate income residents including challenges and next steps.

  15. Alternative Energy and Energy Conservation Patent Income Tax...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Personal) Alternative Energy and Energy Conservation Patent Income Tax Deduction (Personal) < Back Eligibility Residential Savings Category Solar - Passive Solar Water Heat Solar...

  16. Alternative Energy and Energy Conservation Patent Income Tax...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Corporate) Alternative Energy and Energy Conservation Patent Income Tax Deduction (Corporate) < Back Eligibility Commercial Savings Category Solar - Passive Solar Water Heat Solar...

  17. Alabama--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alabama--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 0 9 13 1990's 19,861 32,603 112,311 131,508 228,878 212,895 209,013 214,414 222,000 212,673 2000's 201,081 200,862 202,002 194,339 165,630 152,902 145,762 134,451 125,502 109,214 2010's 101,487 84,270 87,398 75,660 70,827 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  18. Alaska--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Alaska--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 72,813 71,946 1980's 63,355 71,477 66,852 68,776 68,315 62,454 63,007 69,656 101,440 122,595 1990's 144,064 171,665 216,377 233,198 224,301 113,552 126,051 123,854 133,111 125,841 2000's 263,958 262,937 293,580 322,010 334,125 380,568 354,816 374,204 388,188 357,490 2010's 370,148 364,702 307,306

  19. Federal Offshore--Texas Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) Federal Offshore--Texas Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 88,258 249,255 554,076 1980's 696,181 775,351 875,204 844,711 909,778 834,870 1,054,537 1,232,554 1,278,548 1,346,940 1990's 1,447,164 1,396,001 1,332,883 1,276,099 1,308,154 1,283,493 1,338,413 1,286,539 1,180,967 1,157,128 2000's 1,136,062 NA NA NA NA NA NA NA NA NA 2010's NA NA 0 0 0 - = No Data

  20. US--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet)

    U.S. Energy Information Administration (EIA) Indexed Site

    Gross Withdrawals (Million Cubic Feet) US--State Offshore Natural Gas Gross Withdrawals (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 755,671 780,911 1980's 747,743 702,765 693,177 552,610 513,279 446,237 403,050 406,377 434,211 459,617 1990's 462,652 458,800 552,294 607,435 704,469 489,576 597,239 590,815 615,249 558,692 2000's 655,609 678,580 696,905 710,240 680,911 684,671 629,652 618,042 653,704 586,953 2010's 575,601 549,151 489,505

  1. ASYMPTOTICALLY FREE GAUGE THEORIES - I* David J. Gross+ National Accelerator Laboratory

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    national accelerator laboratory NAL-PUB-73/49-THY July, 1973 ASYMPTOTICALLY FREE GAUGE THEORIES - I* David J. Gross+ National Accelerator Laboratory and Joseph Henry Laboratories Princeton University Princeton, New Jersey 08540 and Frank Wilczek Joseph Henry Laboratories Princeton University Princeton, New Jersey 08540 * Research supported in part by the United States Air Force Office of Scientific Research under Contract F-44620-71-6-0180 t Alfred P. Sloan Foundation Research Fellow 2% Oaerated

  2. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  3. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  4. 55,"Aberdeen City of",5,1,479437,"Taxes Other Than Income Taxes...

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Units (line 14, less line 19)" 7977,"Hamilton City of",5,1,0,"Taxes Other Than Income Taxes, Operating Income (408.1)" 7977,"Hamilton City of",5,2,0,"Income Taxes, Operating ...

  5. 55,"Aberdeen City of",5,1,482619,"Taxes Other Than Income Taxes...

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Units (line 14, less line 19)" 7977,"Hamilton City of",5,1,0,"Taxes Other Than Income Taxes, Operating Income (408.1)" 7977,"Hamilton City of",5,2,0,"Income Taxes, Operating ...

  6. ,"Maryland Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  7. ,"Michigan Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  8. ,"Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  9. ,"Missouri Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  10. ,"Montana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  11. ,"Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    from Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  12. ,"New Mexico Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1989" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  13. ,"New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  14. ,"New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Oil Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  15. ,"New Mexico Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New Mexico Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  16. ,"New York Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    from Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","New York Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  17. ,"North Dakota Natural Gas Gross Withdrawals from Gas Wells (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Gas Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from Gas Wells (MMcf)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  18. ,"North Dakota Natural Gas Gross Withdrawals from Oil Wells (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Oil Wells (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from Oil Wells (MMcf)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  19. ,"North Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","North Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  20. ,"Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  1. ,"Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  2. ,"Pennsylvania Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1991" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  3. ,"Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  4. ,"South Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","South Dakota Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  5. ,"Tennessee Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  6. ,"Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1090_stx_2a.xls"

  7. ,"Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  8. ,"U.S. Natural Gas Gross Withdrawals Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","U.S. Natural Gas Gross Withdrawals Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1090_nus_2a.xls" ,"Available

  9. ,"Utah Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  10. ,"Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  11. ,"West Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","West Virginia Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  12. ,"Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  13. ,"Alabama Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1090_sal_2a.xls"

  14. ,"Alaska Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1090_sak_2a.xls"

  15. ,"California Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1090_sca_2a.xls"

  16. ,"California Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1989" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  17. ,"California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  18. ,"Colorado Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1989" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  19. ,"Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  20. ,"Florida Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1989" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  1. ,"Florida Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  2. ,"Illinois Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1991" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  3. ,"Illinois Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  4. ,"Indiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  5. ,"Kansas Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1989" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  6. ,"Kansas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  7. ,"Kentucky Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    from Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  8. ,"Louisiana Natural Gas Gross Withdrawals Total Offshore (MMcf)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Total Offshore (MMcf)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals Total Offshore (MMcf)",1,"Annual",2014 ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File Name:","na1090_sla_2a.xls"

  9. ,"Louisiana Natural Gas Gross Withdrawals and Production"

    U.S. Energy Information Administration (EIA) Indexed Site

    and Production" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals and Production",10,"Monthly","2/2016","1/15/1989" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  10. ,"Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)"

    U.S. Energy Information Administration (EIA) Indexed Site

    Shale Gas (Million Cubic Feet)" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet)",1,"Monthly","2/2016" ,"Release Date:","4/29/2016" ,"Next Release Date:","5/31/2016" ,"Excel File

  11. Drivers of U.S. Household Energy Consumption, 1980-2009 - Energy...

    U.S. Energy Information Administration (EIA) Indexed Site

    This is equivalent to an average annual growth of 1.1% and 1.8%, respectively. As a result, the aggregate energy intensity per household and per square foot declined by 24.2% and ...

  12. Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010

    Broader source: Energy.gov [DOE]

    The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices...

  13. How Do You Encourage Everyone in Your Household to Save Energy?

    Broader source: Energy.gov [DOE]

    Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people—be they roommates, spouses, children, or maybe even...

  14. Tailored Marketing for Low-income and Under-Represented Population...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Tailored Marketing for Low-income and Under-Represented Population Segments (201) Tailored Marketing for Low-income and Under-Represented Population Segments (201) Better Buildings ...

  15. Competition Helps Kids Learn About Energy and Save Their Households Some

    Energy Savers [EERE]

    Money | Department of Energy Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy

  16. Income Tax Deduction for the Installation of Building Insulation

    Broader source: Energy.gov [DOE]

    A residential taxpayer is entitled to an Indiana income tax deduction on the materials and labor used to install insulation in a taxpayer’s principal place of residence in Indiana. 

  17. Income Tax Deduction for Energy-Efficient Products | Department...

    Broader source: Energy.gov (indexed) [DOE]

    may deduct from their taxable personal income an amount equal to 20% of the sales taxes paid for certain energy efficient equipment. The incentive is capped at 500. This...

  18. The Farmer's Conundrum: Income from Biofuels or Protect the Soil?

    Broader source: Energy.gov [DOE]

    Selling crop residues for bioenergy could provide farmers with an extra source of income, but leaving some residue on the fields has benefits too. So how can land managers find this balance?

  19. Empire District Electric- Low Income New Homes Program

    Broader source: Energy.gov [DOE]

    Empire District Electric offers rebates for energy efficient measures and appliances in new, low-income homes. Rebates are available for several types of building insulation, heat pumps, central...

  20. Figure ES2. Annual Indices of Real Disposable Income, Vehicle...

    U.S. Energy Information Administration (EIA) Indexed Site

    ES2 Figure ES2. Annual Indices of Real Disposable Income, Vehicle-Miles Traveled, Consumer Price Index (CPI-U), and Real Average Retail Gasoline Price, 1978-2004, 1985100...

  1. Better Buildings Program San Jose -- Serving Moderate Income Residents |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Program San Jose -- Serving Moderate Income Residents Better Buildings Program San Jose -- Serving Moderate Income Residents Provides an overview of the program components and goals, including the whole neighborhood approach pilot which aims to streamline participant, contractor, and administration processes for neighborhood retrofitting in order to reduce high transaction costs created by the current one-off delivery model. PDF icon San Jose Program Presentation More

  2. Development of the household sample for furnace and boilerlife-cycle cost analysis

    SciTech Connect (OSTI)

    Whitehead, Camilla Dunham; Franco, Victor; Lekov, Alex; Lutz, Jim

    2005-05-31

    Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

  3. Table 4

    U.S. Energy Information Administration (EIA) Indexed Site

    9. Mean Annual Electricity Consumption for Lighting, by Family Income by Number of Household Members, 1993 (Kilowatthours) Number of Household Members Family Income All Households...

  4. Wind Development Found to Increase County-Level Personal Income |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Development Found to Increase County-Level Personal Income Wind Development Found to Increase County-Level Personal Income January 10, 2013 - 2:21pm Addthis This is an excerpt from the Fourth Quarter 2012 edition of the Wind Program R&D Newsletter. The U.S. Department of Energy's (DOE's) Lawrence Berkley National Laboratory and National Renewable Energy Laboratory (NREL) joined forces with the U.S. Department of Agriculture (USDA) to complete a first-of-its-kind

  5. Revenue phase-in plans equal deferred taxable income

    SciTech Connect (OSTI)

    Beck, D.E.

    1994-04-01

    Recently, utilities seeking rate increases have submitted innovative petitions for phase-in rate relief to state regulators. According to the Edison Electric Institute, the industry has seen almost 80 phase-in rate orders issued nation-wide in the last six years. For financial reporting purposes, deferred revenues under phase-in plans must be recognized as current income in the first year of the phase-in. The Internal Revenue Service (IRS) at the Industry Coordinator level, however, recently accepted the position that deferred phase-in revenues accrued for book purposes are not immediately taxable income to the utility.

  6. NYSERDA's Green Jobs-Green New York Program: Extending Energy Efficiency Financing To Underserved Households

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

    The New York legislature passed the Green Jobs-Green New York (GJGNY) Act in 2009. Administered by the New York State Energy Research and Development Authority (NYSERDA), GJGNY programs provide New Yorkers with access to free or low-cost energy assessments,1 energy upgrade services,2 low-cost financing, and training for various 'green-collar' careers. Launched in November 2010, GJGNY's residential initiative is notable for its use of novel underwriting criteria to expand access to energy efficiency financing for households seeking to participate in New York's Home Performance with Energy Star (HPwES) program.3 The GJGNY financing program is a valuable test of whether alternatives to credit scores can be used to responsibly expand credit opportunities for households that do not qualify for traditional lending products and, in doing so, enable more households to make energy efficiency upgrades.

  7. "Table HC15.3 Household Characteristics by Four Most Populated States, 2005"

    U.S. Energy Information Administration (EIA) Indexed Site

    3 Household Characteristics by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Household Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Household Size" "1 Person",30,1.8,1.9,2,3.2 "2 Persons",34.8,2.2,2.3,2.4,3.2 "3 Persons",18.4,1.1,1.3,1.2,1.8

  8. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    6 Weatherization Costs and Savings - DOE Weatherization program requires that States spend no more than an average of $6,572 per household in PY 2011. All States are using energy audits or priority lists to determine the most cost-effective weatherization measures. - DOE weatherization created an average energy savings of $437 per household, reduced household annual annual consumption by 35% and returned savings of $1.80 per every $1 invested. Source(s): DOE, Weatherization and Intergovernmental

  9. Average U.S. household to spend $710 less on gasoline during 2015

    U.S. Energy Information Administration (EIA) Indexed Site

    Average U.S. household to spend $710 less on gasoline during 2015 Even with the recent increases in gasoline prices, the average U.S. household is still expected save $710 in gasoline costs this year compared with what was paid at the pump in 2014. In its new monthly forecast, the U.S. Energy Information Administration said the national average price for regular gasoline is expected to be $2.39 per gallon this year. That's almost $1 less than the $3.36 average in 2014. Lower crude oil prices

  10. Average household expected to save $675 at the pump in 2015

    U.S. Energy Information Administration (EIA) Indexed Site

    Average household expected to save $675 at the pump in 2015 Although retail gasoline prices have risen in recent weeks U.S. consumers are still expected to save about $675 per household in motor fuel costs this year. In its new monthly forecast, the U.S. Energy Information Administration says the average pump price for regular grade gasoline in 2015 will be $2.43 per gallon. That's about 93 cents lower than last year's average. The savings for consumers will be even bigger during the

  11. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Kingston Creek Hydro Project Powers 100 Households EERE Success Story-Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada Controls, LLC used a low-interest loan from the Nevada State Office of Energy's Revolving Loan Fund to help construct a hydropower project in the small Nevada town of Kingston. The Kingston Creek Project-benefitting the Young Brothers Ranch-is a 175-kilowatt hydro generation plant

  12. Drivers of U.S. Household Energy Consumption, 1980-2009

    U.S. Energy Information Administration (EIA) Indexed Site

    Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

  13. QER- Comment of Low-income Energy Affordability Network [MA

    Broader source: Energy.gov [DOE]

    Thank you, Secretary Moniz for the opportunity to submit testimony, I am entering this testimony to call attention to the Secretary and DOE staff, that DOE has operated a successful energy efficiency program for low income renters and home owners since DOE’s creation as a department, that leverages hundreds of millions of dollars in utility and other governmental and private investments...

  14. Family Moderate Income Homeowners In New York State

    Broader source: Energy.gov [DOE]

    "Family Moderate Income Homeowners In New York State: Enhancing Resource Accessibility Through Process Improvement and Targeted Outreach," by Residential Energy Efficiency Solutions, July 10, 2012, Arlington, Virginia. Provides an overview of broadening accessibility to financing through process improvement and targeted outreach.

  15. Slide 1

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Need 3 Significant number of low-income customers. * 12% of families below federal poverty level. * 18% of households receive food stamps. * 34% have household incomes income...

  16. Effects of federal income taxes on the cash flow, operating revenue, and net income of electric utilities

    SciTech Connect (OSTI)

    Moore, J.T.

    1982-01-01

    The idea to do this research was suggested by the efforts of some consumer groups and others to seek passage of a law in the United States to exempt investor-owned electric utilities from federal income taxes. The goal of the consumer groups is to reduce the charges to utility customers (which is measured in this study by the amount of the operating revenues of the utilities) while not causing any harm to the utilities. The population of interest consisted of all investor-owned electric utilities included on a current Compustat utility tape. In the analysis of the data, the changes in cash flow, operating revenue, and net income were summarized by the 89 utilities as a total group and by the division of the utilities into smaller groups or combinations which used the same accounting methods during the test period. The results of this research suggest the following conclusions concerning the change to a situation in which electric utilities are not subject to federal income taxes: (1) as a group, the decrease in cash flow would be significant, (2) as a group, the decrease in operating revenue (charges to customers) would not be significant, (3) as a group, the increase in net income would be significant, and (4) in analyzing the effects of any financial adjustments or changes on electric utilities, the accounting policies used to the utilities are an important factor.

  17. Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose

    Broader source: Energy.gov [DOE]

    In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to...

  18. Table 2. Real Gross Domestic Product Growth Trends, Projected vs. Actual

    U.S. Energy Information Administration (EIA) Indexed Site

    Real Gross Domestic Product Growth Trends, Projected vs. Actual Projected Real GDP Growth Trend (cumulative average percent growth in projected real GDP from first year shown for each AEO) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 3.09 3.15 2.86 2.78 2.73 2.65 2.62 2.60 2.56 2.53 2.52 2.49 2.45 2.41 2.40 2.36 2.32 2.29 AEO 1995 3.66 2.77 2.53 2.71 2.67 2.61 2.55 2.48 2.46 2.45 2.45 2.43 2.39 2.35 2.31 2.27 2.24 AEO 1996 2.61

  19. Other States Natural Gas Gross Withdrawals from Oil Wells (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Oil Wells (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Oil Wells (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1991 3,459 3,117 3,336 1,781 1,806 1,881 1,841 1,820 1,781 1,699 1,247 1,228 1992 4,284 3,872 4,141 4,027 4,047 3,883 3,964 3,957 3,892 4,169 4,146 4,334 1993 4,123 3,693 4,049 3,865 3,942 3,786 3,915 3,924 3,861 4,146 4,114 4,200 1994 3,639 3,242 3,557 3,409 3,488 3,384 3,552 3,643 3,597 3,796 3,818 3,991 1995 3,937 3,524

  20. Other States Natural Gas Gross Withdrawals from Shale Gas (Million Cubic

    U.S. Energy Information Administration (EIA) Indexed Site

    Feet) Shale Gas (Million Cubic Feet) Other States Natural Gas Gross Withdrawals from Shale Gas (Million Cubic Feet) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 13,204 11,926 13,204 12,778 13,204 12,778 13,204 13,204 12,778 13,204 12,778 13,204 2008 12,755 11,932 12,755 12,343 12,755 12,343 12,755 12,755 12,343 12,755 12,343 12,755 2009 12,222 11,039 12,222 11,827 12,222 11,827 12,222 12,222 11,827 12,222 11,827 12,222 2010 11,842 10,659 11,705 11,180 11,541 11,189 11,357 11,589

  1. Failure of the gross theory of beta decay in neutron deficient nuclei

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Firestone, R. B.; Schwengner, R.; Zuber, K.

    2015-05-28

    The neutron deficient isotopes 117-121Xe, 117-124Cs, and 122-124Ba were produced by a beam of 28Si from the LBNL SuperHILAC on a target of natMo. The isotopes were mass separated and their beta decay schemes were measured with a Total Absorption Spectrometer (TAS). The beta strengths derived from these data decreased dramatically to levels above ≈1 MeV for the even-even decays; 3–4 MeV for even-Z, odd-N decays; 4–5 MeV for the odd-Z, even-N decays; and 7–8 MeV for the odd-Z, odd-N decays. The decreasing strength to higher excitation energies in the daughters contradicts the predictions of the Gross Theory of Betamore » Decay. The integrated beta strengths are instead found to be consistent with shell model predictions where the single-particle beta strengths are divided amoung many low-lying levels. The experimental beta strengths determined here have been used calculate the half-lives of 143 neutron deficient nuclei with Z=51–64 to a precision of 20% with respect to the measured values.« less

  2. Failure of the gross theory of beta decay in neutron deficient nuclei

    SciTech Connect (OSTI)

    Firestone, R. B.; Schwengner, R.; Zuber, K.

    2015-05-28

    The neutron deficient isotopes 117-121Xe, 117-124Cs, and 122-124Ba were produced by a beam of 28Si from the LBNL SuperHILAC on a target of natMo. The isotopes were mass separated and their beta decay schemes were measured with a Total Absorption Spectrometer (TAS). The beta strengths derived from these data decreased dramatically to levels above ?1 MeV for the even-even decays; 34 MeV for even-Z, odd-N decays; 45 MeV for the odd-Z, even-N decays; and 78 MeV for the odd-Z, odd-N decays. The decreasing strength to higher excitation energies in the daughters contradicts the predictions of the Gross Theory of Beta Decay. The integrated beta strengths are instead found to be consistent with shell model predictions where the single-particle beta strengths are divided amoung many low-lying levels. The experimental beta strengths determined here have been used calculate the half-lives of 143 neutron deficient nuclei with Z=5164 to a precision of 20% with respect to the measured values.

  3. Weak decay processes in pre-supernova core evolution within the gross theory

    SciTech Connect (OSTI)

    Ferreira, R. C.; Dimarco, A. J.; Samana, A. R.; Barbero, C. A.

    2014-03-20

    The beta decay and electron capture rates are of fundamental importance in the evolution of massive stars in a pre-supernova core. The beta decay process gives its contribution by emitting electrons in the plasma of the stellar core, thereby increasing pressure, which in turn increases the temperature. From the other side, the electron capture removes free electrons from the plasma of the star core contributing to the reduction of pressure and temperature. In this work we calculate the beta decay and electron capture rates in stellar conditions for 63 nuclei of relevance in the pre-supernova stage, employing Gross Theory as the nuclear model. We use the abundances calculated with the Saha equations in the hypothesis of nuclear statistical equilibrium to evaluate the time derivative of the fraction of electrons. Our results are compared with other evaluations available in the literature. They have shown to be one order less or equal than the calculated within other models. Our results indicate that these differences may influence the evolution of the star in the later stages of pre-supernova.

  4. Oregon State Energy-Efficiency Appliance Rebate Program Helps Low-Income Families

    Broader source: Energy.gov [DOE]

    Statewide program provides low-income homeowners with rebates on money-saving, energy-efficient appliances.

  5. Low Income Consumer Utility Issues: A National Perspective

    SciTech Connect (OSTI)

    Eisenberg, J

    2001-03-26

    This report has been prepared to provide low-income advocates and other stakeholders information on the energy burden faced by low-income customers and programs designed to alleviate that burden in various states. The report describes programs designed to lower payments, manage arrearages, weatherize and provide other energy efficiency measures, educate consumers, increase outreach to the target It discusses the costs and benefits of the population, and evaluate the programs. various options--to the degree this information is available--and describes attempts to quantify benefits that have heretofore not been quantified. The purpose of this report is to enable the low-income advocates and others to assess the options and design program most suitable for the citizens of their states or jurisdictions. It is not the authors' intent to recommend a particular course of action but, based on our broad experience in the field, to provide the information necessary for others to do so. We would be happy to answer any questions or provide further documentation on any of the material presented herein. The original edition of this report was prepared for the Utah Committee on Consumer Services, pursuant to a contract with the National Consumer Law Center (NCLC), to provide information to the Utah Low-Income Task Force established by the Utah Public Service, Commission. Attachment 1 is drawn from NCLC's 1998 Supplement to its Access to Utility Services; NCLC plans to update this list in 2001, and it will be available then from NCLC. This report has been updated by the authors for this edition.

  6. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

    U.S. Energy Information Administration (EIA) Indexed Site

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

  7. New Tax Regulations Help Further Low Income Solar | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Tax Regulations Help Further Low Income Solar New Tax Regulations Help Further Low Income Solar April 1, 2016 - 2:50pm Addthis Newly published regulations from the IRS will help more low-income residents benefit from solar installations. The IRS issued temporary rules to clarify the Low-Income Housing Tax Credit's (LIHTC) utility allowance regulations, which allow people who fall into the low-income category to receive a tax credit. The final regulations state that utility costs paid by a tenant

  8. Characterization of household hazardous waste from Marin County, California, and New Orleans, Louisiana

    SciTech Connect (OSTI)

    Rathje, W.L.; Wilson, D.C.; Lambou, V.W.; Herndon, R.C.

    1987-09-01

    There is a growing concern that certain constituents of common household products, that are discarded in residential garbage, may be potentially harmful to human health and the environment by adversely affecting the quality of ground and surface water. A survey of hazardous wastes in residential garbage from Marin County, California, and New Orleans, Louisiana, was conducted in order to determine the amount and characteristics of such wastes that are entering municipal landfills. The results of the survey indicate that approximately 642 metric tons of hazardous waste are discarded per year for the New Orleans study area and approximately 259 metric tons are discarded per year for the Marin County study area. Even though the percent of hazardous household waste in the garbage discarded in both study areas was less than 1%, it represents a significant quantity of hazardous waste because of the large volume of garbage involved.

  9. The importance of China's household sector for black carbon emissions - article no. L12708

    SciTech Connect (OSTI)

    Streets, D.G.; Aunan, K.

    2005-06-30

    The combustion of coal and biofuels in Chinese households is a large source of black carbon (BC), representing about 10-15% of total global emissions during the past two decades, depending on the year. How the Chinese household sector develops during the next 50 years will have an important bearing on future aerosol concentrations, because the range of possible outcomes (about 550 Gg yr{sup -1}) is greater than total BC emissions in either the United States or Europe (each about 400-500 Gg yr{sup -1}). In some Intergovernmental Panel on Climate Change scenarios biofuels persist in rural China for at least the next 50 years, whereas in other scenarios a transition to cleaner fuels and technologies effectively mitigates BC emissions. This paper discusses measures and policies that would help this transition and also raises the possibility of including BC emission reductions as a post-Kyoto option for China and other developing countries.

  10. Evaluation of bulk paint worker exposure to solvents at household hazardous waste collection events

    SciTech Connect (OSTI)

    Cameron, M.

    1995-09-01

    In fiscal year 93/94, over 250 governmental agencies were involved in the collection of household hazardous wastes in the State of California. During that time, over 3,237,000 lbs. of oil based paint were collected in 9,640 drums. Most of this was in lab pack drums, which can only hold up to 20 one gallon cans. Cost for disposal of such drums is approximately $1000. In contrast, during the same year, 1,228,000 lbs. of flammable liquid were collected in 2,098 drums in bulk form. Incineration of bulked flammable liquids is approximately $135 per drum. Clearly, it is most cost effective to bulk flammable liquids at household hazardous waste events. Currently, this is the procedure used at most Temporary Household Hazardous Waste Collection Facilities (THHWCFs). THHWCFs are regulated by the Department of Toxic Substances Control (DTSC) under the new Permit-by Rule Regulations. These regulations specify certain requirements regarding traffic flow, emergency response notifications and prevention of exposure to the public. The regulations require that THHWCF operators bulk wastes only when the public is not present. [22 CCR, section 67450.4 (e) (2) (A)].Santa Clara County Environmental Health Department sponsors local THHWCF`s and does it`s own bulking. In order to save time and money, a variance from the regulation was requested and an employee monitoring program was initiated to determine actual exposure to workers. Results are presented.

  11. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    0 2005 Average Energy Expenditures per Household Member and per Square Foot, by Weatherization Eligibility ($2010) Members/ Hhold Hhold Total U.S. Households 780 2.6 0.86 Federally Eligible 617 2.7 1.10 Federally Ineligible 844 2.5 0.82 Below 100% Poverty Line 603 2.7 1.14 Source(s): 1,442 EIA, 2005 Residential Energy Consumption Survey: Household Energy Consumption and Expenditures Tables, Oct. 2008, Table US1 part2; EIA, Annual Energy Review 2010, Oct. 2011, Appendix D, p. 353 for price

  12. Evaluating the income and employment impacts of gas cooling technologies

    SciTech Connect (OSTI)

    Hughes, P.J.; Laitner, S.

    1995-03-01

    The purpose of this study is to estimate the potential employment and income benefits of the emerging market for gas cooling products. The emphasis here is on exports because that is the major opportunity for the U.S. heating, ventilating, and air-conditioning (HVAC) industry. But domestic markets are also important and considered here because without a significant domestic market, it is unlikely that the plant investments, jobs, and income associated with gas cooling exports would be retained within the United States. The prospects for significant gas cooling exports appear promising for a variety of reasons. There is an expanding need for cooling in the developing world, natural gas is widely available, electric infrastructures are over-stressed in many areas, and the cost of building new gas infrastructure is modest compared to the cost of new electric infrastructure. Global gas cooling competition is currently limited, with Japanese and U.S. companies, and their foreign business partners, the only product sources. U.S. manufacturers of HVAC products are well positioned to compete globally, and are already one of the faster growing goods-exporting sectors of the U.S. economy. Net HVAC exports grew by over 800 percent from 1987 to 1992 and currently exceed $2.6 billion annually (ARI 1994). Net gas cooling job and income creation are estimated using an economic input-output model to compare a reference case to a gas cooling scenario. The reference case reflects current policies, practices, and trends with respect to conventional electric cooling technologies. The gas cooling scenario examines the impact of accelerated use of natural gas cooling technologies here and abroad.

  13. Household`s choices of efficiency levels for appliances: Using stated- and revealed-preference data to identify the importance of rebates and financing arrangements

    SciTech Connect (OSTI)

    Train, K.; Atherton, T.

    1994-11-01

    We examine customers` choice between standard and high-efficiency equipment, and the impact of utility incentives such as rebates and loans on this decision. Using data from interviews with 400 households, we identify the factors that customers consider in their choice of efficiency level for appliances and the relative importance of these factors. We build a model that describes customers` choices and can be used to predict choices in future situations under changes in the attributes of appliances and in the utility`s DSM and as part of the appliance-choice component of utilities` end-use forecasting systems. As examples, the model is used to predict the impacts of: doubling the size of rebates, replacing rebates with financing programs, and offering loans and rebates as alternative options for customers.

  14. A structural analysis of natural gas consumption by income class from 1987 to 1993

    SciTech Connect (OSTI)

    Poyer, D.A.

    1996-12-01

    This study had two major objectives: (1) assess and compare changes in natural gas consumption between 1987 and 1993 by income group and (2) assess the potential influence of energy policy on observed changes in natural gas consumption over time and across income groups. This analysis used U.S. Department of Energy (DOE) data files and involved both the generation of simple descriptive statistics and the use of multivariate regression analysis. The consumption of natural gas by the groups was studied over a six-year period. The results showed that: (1) natural gas use was substantially higher for the highest income group than for the two lower income groups and (2) natural gas consumption declined for the lowest and middle income quintiles and increased for the highest income quintile between 1987 and 1990; between 1990 and 1993, consumption increased for the lowest and middle income quintile, but remained relatively constant for the highest income quintile. The relative importance of the structural and variable factors in explaining consumption changes between survey periods varies by income group. The analysis provides two major energy policy implications: (1) natural gas intensity has been the highest for the lowest income group, indicating that this group is more vulnerable to sudden changes in demand-indicator variables, in particular weather-related variables, than increase natural gas consumption, and (2) the fall in natural gas intensity between 1987 and 1993 may indicate that energy policy has had some impact on reducing natural gas consumption. 11 refs., 4 figs., 16 tabs.

  15. Simulation of gross and net erosion of high-Z materials in the DIII-D divertor

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Wampler, William R.; Ding, R.; Stangeby, P. C.; Elder, J. D.; Tskhakaya, D.; Kirschner, A.; Guo, H. Y.; Chan, V. S.; McLean, A. G.; Snyder, P. B.; et al

    2015-12-17

    The three-dimensional Monte Carlo code ERO has been used to simulate dedicated DIII-D experiments in which Mo and W samples with different sizes were exposed to controlled and well-diagnosed divertor plasma conditions to measure the gross and net erosion rates. Experimentally, the net erosion rate is significantly reduced due to the high local redeposition probability of eroded high-Z materials, which according to the modelling is mainly controlled by the electric field and plasma density within the Chodura sheath. Similar redeposition ratios were obtained from ERO modelling with three different sheath models for small angles between the magnetic field and themore » material surface, mainly because of their similar mean ionization lengths. The modelled redeposition ratios are close to the measured value. Decreasing the potential drop across the sheath can suppress both gross and net erosion because sputtering yield is decreased due to lower incident energy while the redeposition ratio is not reduced owing to the higher electron density in the Chodura sheath. Taking into account material mixing in the ERO surface model, the net erosion rate of high-Z materials is shown to be strongly dependent on the carbon impurity concentration in the background plasma; higher carbon concentration can suppress net erosion. As a result, the principal experimental results such as net erosion rate and profile and redeposition ratio are well reproduced by the ERO simulations.« less

  16. Maldives-Program for Scaling Up Renewable Energy in Low Income...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  17. Nepal-Program for Scaling Up Renewable Energy in Low Income Countries...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  18. Honduras-Program for Scaling Up Renewable Energy in Low Income...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  19. Kenya-Program for Scaling Up Renewable Energy in Low Income Countries...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  20. Mali-Program for Scaling Up Renewable Energy in Low Income Countries...

    Open Energy Info (EERE)

    number of low income countries for energy efficiency, renewable energy and access to modern sustainable energy. The SREP stimulates economic growth through the scaled-up...

  1. Tailored Marketing for Low-income and Under-Represented Population Segments (201)

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Peer Exchange Call Series: Tailored Marketing for Low-Income and Under-Represented Population Segments (201), call slides and discussion summary.

  2. California Solar Initiative- Low-Income Solar Water Heating Rebate Program

    Broader source: Energy.gov [DOE]

    The California Public Utilities Commission (CPUC) voted in October 2011 to create the California Solar Initiative (CSI) Thermal Low-Income program for single and multifamily residential properties....

  3. Table HC6.10 Home Appliances Usage Indicators by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total.............................................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day........................................... 8.2 1.4 1.9 1.4 1.0 2.4 2 Times A Day........................................................ 24.6 4.3 7.6 4.3 4.8 3.7 Once a Day............................................................ 42.3 9.9

  4. Table HC6.11 Home Electronics Characteristics by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    1 Home Electronics Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer ................... 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer................................ 75.6 13.8 25.4 14.4 13.2 8.8 Number of Desktop PCs 1.................................................................. 50.3 11.9 17.4 8.5 7.3 5.2

  5. Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model.....................................................

  6. Table HC6.2 Living Space Characteristics by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    2 Living Space Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................... 3.2 1.7 0.8 0.4 0.3 Q 500 to 999....................................................... 23.8 10.2 6.4 3.4 2.3 1.5 1,000 to 1,499................................................. 20.8 5.5 6.3 3.0 3.3 2.6 1,500 to

  7. Table HC6.9 Home Appliances Characteristics by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    HC6.9 Home Appliances Characteristics by Number of Household Members, 2005 Total U.S.............................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Conventional Ovens Use an Oven.................................................. 109.6 29.5 34.4 18.2 15.7 11.8 1................................................................. 103.3 28.4 32.0 17.3 14.7 11.0 2 or More.................................................... 6.2 1.1 2.5 1.0 0.9 0.8 Do Not

  8. Assessment of lead contamination in Bahrain environment. I. Analysis of household paint

    SciTech Connect (OSTI)

    Madany, I.M.; Ali, S.M.; Akhter, M.S.

    1987-01-01

    The analysis of lead in household paint collected from various old buildings in Bahrain is reported. The atomic absorption spectrophotometric method, both flame and flameless (graphite furnace) techniques, were used for the analysis. The concentrations of lead in paint were found in the range 200 to 5700 mg/kg, which are low compared to the limit of 0.5% in UK and 0.06% in USA. Nevertheless, these are hazardous. Recommendations are reported in order to avoid paint containing lead. 17 references, 1 table.

  9. WEEE and portable batteries in residual household waste: Quantification and characterisation of misplaced waste

    SciTech Connect (OSTI)

    Bigum, Marianne; Petersen, Claus; Scheutz, Charlotte

    2013-11-15

    Highlights: • We analyse 26.1 Mg of residual waste from 3129 Danish households. • We quantify and characterise misplaced WEEE and portable batteries. • We compare misplaced WEEE and batteries to collection through dedicated schemes. • Characterisation showed that primarily small WEEE and light sources are misplaced. • Significant amounts of misplaced batteries were discarded as built-in WEEE. - Abstract: A total of 26.1 Mg of residual waste from 3129 households in 12 Danish municipalities was analysed and revealed that 89.6 kg of Waste Electrical and Electronic Equipment (WEEE), 11 kg of batteries, 2.2 kg of toners and 16 kg of cables had been wrongfully discarded. This corresponds to a Danish household discarding 29 g of WEEE (7 items per year), 4 g of batteries (9 batteries per year), 1 g of toners and 7 g of unidentifiable cables on average per week, constituting 0.34% (w/w), 0.04% (w/w), 0.01% (w/w) and 0.09% (w/w), respectively, of residual waste. The study also found that misplaced WEEE and batteries in the residual waste constituted 16% and 39%, respectively, of what is being collected properly through the dedicated special waste collection schemes. This shows that a large amount of batteries are being discarded with the residual waste, whereas WEEE seems to be collected relatively successfully through the dedicated special waste collection schemes. Characterisation of the misplaced batteries showed that 20% (w/w) of the discarded batteries were discarded as part of WEEE (built-in). Primarily alkaline batteries, carbon zinc batteries and alkaline button cell batteries were found to be discarded with the residual household waste. Characterisation of WEEE showed that primarily small WEEE (WEEE directive categories 2, 5a, 6, 7 and 9) and light sources (WEEE directive category 5b) were misplaced. Electric tooth brushes, watches, clocks, headphones, flashlights, bicycle lights, and cables were items most frequently found. It is recommended that these findings are taken into account when designing new or improving existing special waste collection schemes. Improving the collection of WEEE is also recommended as one way to also improve the collection of batteries due to the large fraction of batteries found as built-in. The findings in this study were comparable to other western European studies, suggesting that the recommendations made in this study could apply to other western European countries as well.

  10. The changing character of household waste in the Czech Republic between 1999 and 2009 as a function of home heating methods

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

    Highlights: The character of household waste in the three different types of households were assesed. The quantity, density and composition of household waste were determined. The physicochemical characteristics were determined. The changing character of household waste during past 10 years was described. The potential of energy recovery of household waste in Czech republic was assesed. - Abstract: The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in rural households. Because knowledge about the properties of household waste, as well as its physicochemical characteristics, is very important not only for future waste management, but also for the prediction of the behaviour and influence of the waste on the environment as the country continues to streamline its legislation to the European Unions solid waste mandates, the results of these studies were employed by the Czech Ministry of Environment to optimise the national waste management strategy.

  11. Recovery and separation of high-value plastics from discarded household appliances

    SciTech Connect (OSTI)

    Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J.; Arman, B. |

    1996-03-01

    Argonne National Laboratory is conducting research to develop a cost- effective and environmentally acceptable process for the separation of high-value plastics from discarded household appliances. The process under development has separated individual high purity (greater than 99.5%) acrylonitrile-butadiene-styrene (ABS) and high- impact polystyrene (HIPS) from commingled plastics generated by appliance-shredding and metal-recovery operations. The process consists of size-reduction steps for the commingled plastics, followed by a series of gravity-separation techniques to separate plastic materials of different densities. Individual plastics of similar densities, such as ABS and HIPS, are further separated by using a chemical solution. By controlling the surface tension, the density, and the temperature of the chemical solution we are able to selectively float/separate plastics that have different surface energies. This separation technique has proven to be highly effective in recovering high-purity plastics materials from discarded household appliances. A conceptual design of a continuous process to recover high-value plastics from discarded appliances is also discussed. In addition to plastics separation research, Argonne National Laboratory is conducting research to develop cost-effective techniques for improving the mechanical properties of plastics recovered from appliances.

  12. Survey of Recipients of WAP Services Assessment of Household Budget and Energy Behaviors Pre to Post Weatherization DOE

    SciTech Connect (OSTI)

    Tonn, Bruce Edward; Rose, Erin M.; Hawkins, Beth A.

    2015-10-01

    This report presents results from the national survey of weatherization recipients. This research was one component of the retrospective and Recovery Act evaluations of the U.S. Department of Energy s Weatherization Assistance Program. Survey respondents were randomly selected from a nationally representative sample of weatherization recipients. The respondents and a comparison group were surveyed just prior to receiving their energy audits and then again approximately 18 months post-weatherization. This report focuses on budget issues faced by WAP households pre- and post-weatherization, whether household energy behaviors changed from pre- to post, the effectiveness of approaches to client energy education, and use and knowledge about thermostats.

  13. Microsoft Word - Mont Co Final Report 1-4-13

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    to reduce energy consumption for low-income households through energy efficient upgrades. ... The Weatherization Program helps eligible low-income households lower their energy costs ...

  14. Table HC6.4 Space Heating Characteristics by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    4 Space Heating Characteristics by Number of Household Members, 2005 Total..................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Space Heating Equipment............ 1.2 0.3 0.3 Q 0.2 0.2 Have Main Space Heating Equipment............... 109.8 29.7 34.5 18.2 15.6 11.8 Use Main Space Heating Equipment................. 109.1 29.5 34.4 18.1 15.5 11.6 Have Equipment But Do Not Use It................... 0.8 Q Q Q Q Q Main Heating Fuel and

  15. Table HC6.5 Space Heating Usage Indicators by Number of Household Members, 2005

    U.S. Energy Information Administration (EIA) Indexed Site

    5 Space Heating Usage Indicators by Number of Household Members, 2005 Total U.S. Housing Units.................................. 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Heating Equipment..................... 1.2 0.3 0.3 Q 0.2 0.2 Have Space Heating Equipment....................... 109.8 29.7 34.5 18.2 15.6 11.8 Use Space Heating Equipment........................ 109.1 29.5 34.4 18.1 15.5 11.6 Have But Do Not Use Equipment.................... 0.8 Q Q Q Q Q Space Heating Usage During 2005

  16. Residential energy use and conservation in Venezuela: Results and implications of a household survey in Caracas

    SciTech Connect (OSTI)

    Figueroa, M.J.; Ketoff, A.; Masera, O.

    1992-10-01

    This document presents the final report of a study of residential energy use in Caracas, the capital of Venezuela. It contains the findings of a household energy-use survey held in Caracas in 1988 and examines options for introducing energy conservation measures in the Venezuelan residential sector. Oil exports form the backbone of the Venezuelan economy. Improving energy efficiency in Venezuela will help free domestic oil resources that can be sold to the rest of the world. Energy conservation will also contribute to a faster recovery of the economy by reducing the need for major investments in new energy facilities, allowing the Venezuelan government to direct its financial investments towards other areas of development. Local environmental benefits will constitute an important additional by-product of implementing energy-efficiency policies in Venezuela. Caracas`s residential sector shows great potential for energy conservation. The sector is characterized by high saturation levels of major appliances, inefficiency of appliances available in the market, and by careless patterns of energy use. Household energy use per capita average 6.5 GJ/per year which is higher than most cities in developing countries; most of this energy is used for cooking. Electricity accounts for 41% of all energy use, while LPG and natural gas constitute the remainder. Specific options for inducing energy conservation and energy efficiency in Caracas`s residential sector include energy-pricing policies, fuel switching, particularly from electricity to gas, improving the energy performance of new appliances and customer information. To ensure the accomplishment of an energy-efficiency strategy, a concerted effort by energy users, manufacturers, utility companies, government agencies, and research institutions will be needed.

  17. Chapter 12, Survey Design and Implementation Cross-Cutting Protocols for Estimating Gross Savings: The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Chapter 12: Survey Design and Implementation Cross-Cutting Protocols for Estimating Gross Savings Robert Baumgartner, Tetra Tech Subcontract Report NREL/SR-7A30-53827 April 2013 The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures 12 - 1 Chapter 12 - Table of Contents 1 Introduction ............................................................................................................................ 2 2 The Total Survey Error Framework

  18. DOE Provides $96.4 Million to Low-Income Families for Home Weatherization |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy $96.4 Million to Low-Income Families for Home Weatherization DOE Provides $96.4 Million to Low-Income Families for Home Weatherization July 6, 2006 - 2:50pm Addthis Funding is Second Installment of $243 Million in Total Weatherization Grants for FY 2006 WASHINGTON, D.C. - U.S. Department of Energy (DOE) Secretary Samuel W. Bodman today announced $96.4 million in weatherization program grants to 19 states to make energy efficiency improvements in homes of low-income

  19. Department of Energy Provides Nearly $88 Million to Low-Income Families for

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Home Weatherization | Department of Energy 88 Million to Low-Income Families for Home Weatherization Department of Energy Provides Nearly $88 Million to Low-Income Families for Home Weatherization June 29, 2007 - 2:36pm Addthis Funding is Second Installment of $200 Million in Total Weatherization Grants for FY 2007 WASHINGTON, DC - U.S. Department of Energy (DOE) today announced $88 million in weatherization grants to 20 states to make energy efficiency improvements in homes of low-income

  20. EO 12898: Environmental Justice in Minority Populations and Low-Income Populations (1994)

    Broader source: Energy.gov [DOE]

    To focus Federal attention on the environmental and human health conditions in minority communities and low-income communities with the goal of achieving environmental justice. That order is also...

  1. EO 12898: Environmental Justice in Minority Populations and Low-Income Populations

    Broader source: Energy.gov [DOE]

    To focus Federal attention on the environmental and human health conditions in minority communities and low-income communities with the goal of achieving environmental justice. That order is also...

  2. New Hampshire Electric Co-Op- Low-Income Energy Assistance Grant Program

    Broader source: Energy.gov [DOE]

    The Energy Assistance Program is designed to help NHEC's income-qualified members manage energy use with the goal of lowering total energy costs. Qualified members living in an apartment or house,...

  3. Table 5.8. U.S. Vehicle Fuel Consumption by Family Income, 1994

    U.S. Energy Information Administration (EIA) Indexed Site

    and 1994 Vehicle Characteristics RSE Column Factor: Total 1993 Family Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factor: Less than 5,000 5,000...

  4. Energy data report: Sales, Revenue, and Income of Electric Utilities. Monthly report, October 1981

    SciTech Connect (OSTI)

    Woods, T.F.

    1982-01-19

    This is the last issue of Sales, Revenue, and Income of Electric Utilities. The data contained in this report are being published in Section 10 of the Electric Power Monthly.

  5. http://www.census.gov/

    National Nuclear Security Administration (NNSA)

    People & Households American Community Survey * Estimates * Projections Income | State Median Income * Poverty * Health Insurance International * Genealogy * Census 2000 * More ...

  6. Dual Integrated Appliances as an Energy and Safety Solution for Low Income

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Weatherization Webinar | Department of Energy Dual Integrated Appliances as an Energy and Safety Solution for Low Income Weatherization Webinar Dual Integrated Appliances as an Energy and Safety Solution for Low Income Weatherization Webinar Slides from the Building America webinar presented by the NorthernSTAR team. PDF icon webinar_northernstar_dual_appliances_20111019.pdf More Documents & Publications Building America Expert Meeting: Recommendations for Applying Water Heaters in

  7. Sensitivity of Global Terrestrial Gross Primary Production to Hydrologic States Simulated by the Community Land Model Using Two Runoff Parameterizations

    SciTech Connect (OSTI)

    Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.; Yang, Dawen; Shi, Xiaoying; Mao, Jiafu; Hayes, Daniel J.; Schwalm, C.; Wei, Yaxing; Liu, Shishi

    2014-09-01

    The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically, differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.

  8. Commercial viability of hybrid vehicles : best household use and cross national considerations.

    SciTech Connect (OSTI)

    Santini, D. J.; Vyas, A. D.

    1999-07-16

    Japanese automakers have introduced hybrid passenger cars in Japan and will soon do so in the US. In this paper, we report how we used early computer simulation model results to compare the commercial viability of a hypothetical near-term (next decade) hybrid mid-size passenger car configuration under varying fuel price and driving patterns. The fuel prices and driving patterns evaluated are designed to span likely values for major OECD nations. Two types of models are used. One allows the ''design'' of a hybrid to a specified set of performance requirements and the prediction of fuel economy under a number of possible driving patterns (called driving cycles). Another provides an estimate of the incremental cost of the hybrid in comparison to a comparably performing conventional vehicle. In this paper, the models are applied to predict the NPV cost of conventional gasoline-fueled vehicles vs. parallel hybrid vehicles. The parallel hybrids are assumed to (1) be produced at high volume, (2) use nickel metal hydride battery packs, and (3) have high-strength steel bodies. The conventional vehicle also is assumed to have a high-strength steel body. The simulated vehicles are held constant in many respects, including 0-60 time, engine type, aerodynamic drag coefficient, tire rolling resistance, and frontal area. The hybrids analyzed use the minimum size battery pack and motor to meet specified 0-60 times. A key characteristic affecting commercial viability is noted and quantified: that hybrids achieve the most pronounced fuel economy increase (best use) in slow, average-speed, stop-and-go driving, but when households consistently drive these vehicles under these conditions, they tend to travel fewer miles than average vehicles. We find that hours driven is a more valuable measure than miles. Estimates are developed concerning hours of use of household vehicles versus driving cycle, and the pattern of minimum NPV incremental cost (or benefit) of selecting the hybrid over the conventional vehicle at various fuel prices is illustrated. These results are based on data from various OECD motions on fuel price, annual miles of travel per vehicle, and driving cycles assumed to be applicable in those nations. Scatter in results plotted as a function of average speed, related to details of driving cycles and the vehicles selected for analysis, is discussed.

  9. Household mold and dust allergens: Exposure, sensitization and childhood asthma morbidity

    SciTech Connect (OSTI)

    Gent, Janneane F.; Kezik, Julie M.; Hill, Melissa E.; Tsai, Eling; Li, De-Wei; Leaderer, Brian P.

    2012-10-15

    Background: Few studies address concurrent exposures to common household allergens, specific allergen sensitization and childhood asthma morbidity. Objective: To identify levels of allergen exposures that trigger asthma exacerbations in sensitized individuals. Methods: We sampled homes for common indoor allergens (fungi, dust mites (Der p 1, Der f 1), cat (Fel d 1), dog (Can f 1) and cockroach (Bla g 1)) for levels associated with respiratory responses among school-aged children with asthma (N=1233) in a month-long study. Blood samples for allergy testing and samples of airborne fungi and settled dust were collected at enrollment. Symptoms and medication use were recorded on calendars. Combined effects of specific allergen sensitization and level of exposure on wheeze, persistent cough, rescue medication use and a 5-level asthma severity score were examined using ordered logistic regression. Results: Children sensitized and exposed to any Penicillium experienced increased risk of wheeze (odds ratio [OR] 2.12 95% confidence interval [CI] 1.12, 4.04), persistent cough (OR 2.01 95% CI 1.05, 3.85) and higher asthma severity score (OR 1.99 95% CI 1.06, 3.72) compared to those not sensitized or sensitized but unexposed. Children sensitized and exposed to pet allergen were at significantly increased risk of wheeze (by 39% and 53% for Fel d 1>0.12 {mu}g/g and Can f 1>1.2 {mu}g/g, respectively). Increased rescue medication use was significantly associated with sensitization and exposure to Der p 1>0.10 {mu}g/g (by 47%) and Fel d 1>0.12 {mu}g/g (by 32%). Conclusion: Asthmatic children sensitized and exposed to low levels of common household allergens Penicillium, Der p 1, Fel d 1 and Can f 1 are at significant risk for increased morbidity. - Highlights: Black-Right-Pointing-Pointer Few studies address concurrent allergen exposures, sensitization and asthma morbidity. Black-Right-Pointing-Pointer Children with asthma were tested for sensitivity to common indoor allergens. Black-Right-Pointing-Pointer Homes were sampled for these allergens and asthma morbidity monitored during the subsequent month. Black-Right-Pointing-Pointer Children exposed and sensitized to Penicillium, Der p, Fel d, Can f risk increased asthma morbidity. Black-Right-Pointing-Pointer These children might benefit from targeted intervention strategies.

  10. Municipal solid waste generation in municipalities: Quantifying impacts of household structure, commercial waste and domestic fuel

    SciTech Connect (OSTI)

    Lebersorger, S.; Beigl, P.

    2011-09-15

    Waste management planning requires reliable data concerning waste generation, influencing factors on waste generation and forecasts of waste quantities based on facts. This paper aims at identifying and quantifying differences between different municipalities' municipal solid waste (MSW) collection quantities based on data from waste management and on socio-economic indicators. A large set of 116 indicators from 542 municipalities in the Province of Styria was investigated. The resulting regression model included municipal tax revenue per capita, household size and the percentage of buildings with solid fuel heating systems. The model explains 74.3% of the MSW variation and the model assumptions are met. Other factors such as tourism, home composting or age distribution of the population did not significantly improve the model. According to the model, 21% of MSW collected in Styria was commercial waste and 18% of the generated MSW was burned in domestic heating systems. While the percentage of commercial waste is consistent with literature data, practically no literature data are available for the quantity of MSW burned, which seems to be overestimated by the model. The resulting regression model was used as basis for a waste prognosis model (Beigl and Lebersorger, in preparation).

  11. LCA for household waste management when planning a new urban settlement

    SciTech Connect (OSTI)

    Slagstad, Helene; Brattebo, Helge

    2012-07-15

    Highlights: Black-Right-Pointing-Pointer Household waste management of a new carbon neutral settlement. Black-Right-Pointing-Pointer EASEWASTE as a LCA tool to compare different centralised and decentralised solutions. Black-Right-Pointing-Pointer Environmental benefit or close to zero impact in most of the categories. Black-Right-Pointing-Pointer Paper and metal recycling important for the outcome. Black-Right-Pointing-Pointer Discusses the challenges of waste prevention planning. - Abstract: When planning for a new urban settlement, industrial ecology tools like scenario building and life cycle assessment can be used to assess the environmental quality of different infrastructure solutions. In Trondheim, a new greenfield settlement with carbon-neutral ambitions is being planned and five different scenarios for the waste management system of the new settlement have been compared. The results show small differences among the scenarios, however, some benefits from increased source separation of paper and metal could be found. The settlement should connect to the existing waste management system of the city, and not resort to decentralised waste treatment or recovery methods. However, as this is an urban development project with ambitious goals for lifestyle changes, effort should be put into research and initiatives for proactive waste prevention and reuse issues.

  12. Estimating household fuel oil/kerosine, natural gas, and LPG prices by census region

    SciTech Connect (OSTI)

    Poyer, D.A.; Teotia, A.P.S.

    1994-08-01

    The purpose of this research is to estimate individual fuel prices within the residential sector. The data from four US Department of Energy, Energy Information Administration, residential energy consumption surveys were used to estimate the models. For a number of important fuel types - fuel oil, natural gas, and liquefied petroleum gas - the estimation presents a problem because these fuels are not used by all households. Estimates obtained by using only data in which observed fuel prices are present would be biased. A correction for this self-selection bias is needed for estimating prices of these fuels. A literature search identified no past studies on application of the selectivity model for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas. This report describes selectivity models that utilize the Dubin/McFadden correction method for estimating prices of residential fuel oil/kerosine, natural gas, and liquefied petroleum gas in the Northeast, Midwest, South, and West census regions. Statistically significant explanatory variables are identified and discussed in each of the models. This new application of the selectivity model should be of interest to energy policy makers, researchers, and academicians.

  13. Influence of assumptions about household waste composition in waste management LCAs

    SciTech Connect (OSTI)

    Slagstad, Helene, E-mail: helene.slagstad@ntnu.no [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway); Brattebo, Helge [Department of Hydraulic and Environmental Engineering, Norwegian University of Science and Technology, N-7491 Trondheim (Norway)

    2013-01-15

    Highlights: Black-Right-Pointing-Pointer Uncertainty in waste composition of household waste. Black-Right-Pointing-Pointer Systematically changed waste composition in a constructed waste management system. Black-Right-Pointing-Pointer Waste composition important for the results of accounting LCA. Black-Right-Pointing-Pointer Robust results for comparative LCA. - Abstract: This article takes a detailed look at an uncertainty factor in waste management LCA that has not been widely discussed previously, namely the uncertainty in waste composition. Waste composition is influenced by many factors; it can vary from year to year, seasonally, and with location, for example. The data publicly available at a municipal level can be highly aggregated and sometimes incomplete, and performing composition analysis is technically challenging. Uncertainty is therefore always present in waste composition. This article performs uncertainty analysis on a systematically modified waste composition using a constructed waste management system. In addition the environmental impacts of several waste management strategies are compared when applied to five different cities. We thus discuss the effect of uncertainty in both accounting LCA and comparative LCA. We found the waste composition to be important for the total environmental impact of the system, especially for the global warming, nutrient enrichment and human toxicity via water impact categories.

  14. The evolving price of household LED lamps: Recent trends and historical comparisons for the US market

    SciTech Connect (OSTI)

    Gerke, Brian F.; Ngo, Allison T.; Alstone, Andrea L.; Fisseha, Kibret S.

    2014-10-14

    In recent years, household LED light bulbs (LED A lamps) have undergone a dramatic price decline. Since late 2011, we have been collecting data, on a weekly basis, for retail offerings of LED A lamps on the Internet. The resulting data set allows us to track the recent price decline in detail. LED A lamp prices declined roughly exponentially with time in 2011-2014, with decline rates of 28percent to 44percent per year depending on lumen output, and with higher-lumen lamps exhibiting more rapid price declines. By combining the Internet price data with publicly available lamp shipments indices for the US market, it is also possible to correlate LED A lamp prices against cumulative production, yielding an experience curve for LED A lamps. In 2012-2013, LED A lamp prices declined by 20-25percent for each doubling in cumulative shipments. Similar analysis of historical data for other lighting technologies reveals that LED prices have fallen significantly more rapidly with cumulative production than did their technological predecessors, which exhibited a historical decline of 14-15percent per doubling of production.

  15. Status of not-in-kind refrigeration technologies for household space conditioning, water heating and food refrigeration

    SciTech Connect (OSTI)

    Bansal, Pradeep; Vineyard, Edward Allan; Abdelaziz, Omar

    2012-01-01

    This paper presents a review of the next generation not-in-kind technologies to replace conventional vapor compression refrigeration technology for household applications. Such technologies are sought to provide energy savings or other environmental benefits for space conditioning, water heating and refrigeration for domestic use. These alternative technologies include: thermoacoustic refrigeration, thermoelectric refrigeration, thermotunneling, magnetic refrigeration, Stirling cycle refrigeration, pulse tube refrigeration, Malone cycle refrigeration, absorption refrigeration, adsorption refrigeration, and compressor driven metal hydride heat pumps. Furthermore, heat pump water heating and integrated heat pump systems are also discussed due to their significant energy saving potential for water heating and space conditioning in households. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Both thermoelectric and magnetic technologies look relatively attractive due to recent developments in the materials and prototypes being manufactured.

  16. Fixed conditions for achieving the real-valued partition function of one-dimensional Gross-Pitaevskii equation coupled with time-dependent potential

    SciTech Connect (OSTI)

    Prayitno, T. B.

    2014-03-24

    We have imposed the conditions in order to preserve the real-valued partition function in the case of onedimensional Gross-Pitaevskii equation coupled by time-dependent potential. In this case we have solved the Gross-Pitaevskii equation by means of the time-dependent perturbation theory by extending the previous work of Kivshar et al. [Phys. Lett A 278, 225–230 (2001)]. To use the method, we have treated the equation as the macroscopic quantum oscillator and found that the expression of the partition function explicitly has complex values. In fact, we have to choose not only the appropriate functions but also the suitable several values of the potential to keep the real-valued partition function.

  17. Cost comparison between private and public collection of residual household waste: Multiple case studies in the Flemish region of Belgium

    SciTech Connect (OSTI)

    Jacobsen, R.; Buysse, J.; Gellynck, X.

    2013-01-15

    Highlights: Black-Right-Pointing-Pointer The goal is to compare collection costs for residual household waste. Black-Right-Pointing-Pointer We have clustered all municipalities in order to find mutual comparable pairs. Black-Right-Pointing-Pointer Each pair consists of one private and one public operating waste collection program. Black-Right-Pointing-Pointer All cases show that private service has lower costs than public service. Black-Right-Pointing-Pointer Municipalities were contacted to identify the deeper causes for the waste management program. - Abstract: The rising pressure in terms of cost efficiency on public services pushes governments to transfer part of those services to the private sector. A trend towards more privatizing can be noticed in the collection of municipal household waste. This paper reports the findings of a research project aiming to compare the cost between the service of private and public collection of residual household waste. Multiple case studies of municipalities about the Flemish region of Belgium were conducted. Data concerning the year 2009 were gathered through in-depth interviews in 2010. In total 12 municipalities were investigated, divided into three mutual comparable pairs with a weekly and three mutual comparable pairs with a fortnightly residual waste collection. The results give a rough indication that in all cases the cost of private service is lower than public service in the collection of household waste. Albeit that there is an interest in establishing whether there are differences in the costs and service levels between public and private waste collection services, there are clear difficulties in establishing comparisons that can be made without having to rely on a large number of assumptions and corrections. However, given the cost difference, it remains the responsibility of the municipalities to decide upon the service they offer their citizens, regardless the cost efficiency: public or private.

  18. Natural Gas Gross Withdrawals

    U.S. Energy Information Administration (EIA) Indexed Site

    Federal Offshore Gulf of Mexico 122,038 116,075 106,086 112,137 108,556 101,200 1997-2016 Kansas 23,819 23,559 22,451 22,896 22,535 20,900 1991-2016 Louisiana 164,270 166,973 ...

  19. What is Gross Up?

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    reimbursement amount. You do not see the money in your pocket, but rather it offsets taxes that would have reduced the payment if we had not paid you the additional amount. For...

  20. Natural Gas Gross Withdrawals

    U.S. Energy Information Administration (EIA) Indexed Site

    2010 2011 2012 2013 2014 2015 View History U.S. 26,816,085 28,479,026 29,542,313 29,522,551 31,345,546 32,965,038 1936-2015 U.S. Offshore 2,875,945 2,416,644 2,044,643 1,859,469 1,818,267 1977-2014 U.S. State Offshore 575,601 549,151 489,505 505,318 514,809 1978-2014 Federal Offshore U.S. 2,300,344 1,867,492 1,555,138 1,354,151 1,303,458 1977-2014 Alaska 3,197,100 3,162,922 3,164,791 3,215,358 3,168,566 3,175,163 1967-2015 Alaska Onshore 2,826,952 2,798,220 2,857,485 2,882,956 2,803,429

  1. Natural Gas Gross Withdrawals

    U.S. Energy Information Administration (EIA) Indexed Site

    Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 View History U.S. 2,750,252 2,817,792 2,743,783 2,823,547 2,823,205 2,668,567 1973-2016 Alaska 261,150 279,434 289,770 304,048 298,809 273,296 1991-2016 Arkansas 81,546 83,309 79,289 80,509 77,827 71,965 1991-2016 California 18,928 18,868 18,261 18,749 18,796 17,195 1991-2016 Colorado 138,325 144,845 139,733 142,189 143,369 134,150 1991-2016 Federal Offshore Gulf of Mexico 122,038 116,075 106,086 112,137 108,556 101,200 1997-2016 Kansas 23,819 23,559

  2. Natural Gas Gross Withdrawals

    U.S. Energy Information Administration (EIA) Indexed Site

    Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2010 2011 2012 2013 2014 2015 View History U.S. 26,816,085 28,479,026 29,542,313 29,522,551 31,345,546 32,965,038 1936-2015 U.S. Offshore 2,875,945 2,416,644 2,044,643 1,859,469 1,818,267 1977-2014 U.S. State Offshore 575,601 549,151 489,505 505,318 514,809 1978-2014 Federal Offshore U.S.

  3. Natural Gas Gross Withdrawals

    Gasoline and Diesel Fuel Update (EIA)

    Feet Monthly-Million Cubic Feet per Day Annual-Million Cubic Feet Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

  4. A life cycle approach to the management of household food waste - A Swedish full-scale case study

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2011-08-15

    Research Highlights: > The comparison of three different methods for management of household food waste show that anaerobic digestion provides greater environmental benefits in relation to global warming potential, acidification and ozone depilation compared to incineration and composting of food waste. Use of produced biogas as car fuel provides larger environmental benefits compared to a use of biogas for heat and power production. > The use of produced digestate from the anaerobic digestion as substitution for chemical fertilizer on farmland provides avoidance of environmental burdens in the same ratio as the substitution of fossil fuels with produced biogas. > Sensitivity analyses show that results are highly sensitive to assumptions regarding the environmental burdens connected to heat and energy supposedly substituted by the waste treatment. - Abstract: Environmental impacts from incineration, decentralised composting and centralised anaerobic digestion of solid organic household waste are compared using the EASEWASTE LCA-tool. The comparison is based on a full scale case study in southern Sweden and used input-data related to aspects such as source-separation behaviour, transport distances, etc. are site-specific. Results show that biological treatment methods - both anaerobic and aerobic, result in net avoidance of GHG-emissions, but give a larger contribution both to nutrient enrichment and acidification when compared to incineration. Results are to a high degree dependent on energy substitution and emissions during biological processes. It was seen that if it is assumed that produced biogas substitute electricity based on Danish coal power, this is preferable before use of biogas as car fuel. Use of biogas for Danish electricity substitution was also determined to be more beneficial compared to incineration of organic household waste. This is a result mainly of the use of plastic bags in the incineration alternative (compared to paper bags in the anaerobic) and the use of biofertiliser (digestate) from anaerobic treatment as substitution of chemical fertilisers used in an incineration alternative. Net impact related to GWP from the management chain varies from a contribution of 2.6 kg CO{sub 2}-eq/household and year if incineration is utilised, to an avoidance of 5.6 kg CO{sub 2}-eq/household and year if choosing anaerobic digestion and using produced biogas as car fuel. Impacts are often dependent on processes allocated far from the control of local decision-makers, indicating the importance of a holistic approach and extended collaboration between agents in the waste management chain.

  5. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    3 Households Weatherized and Weatherization Eligibility by Year (Million) (1) Federally Federally Below 125% Below 150% Total DOE Eligible (2) Ineligible Poverty Line Poverty Line Households 1977 0.025 - - - - 74.8 1980 0.181 - - - - 79.6 1985 0.125 - - - - 87.9 1987 0.100 - - - - 90.5 1990 0.085 27.9 66.1 18.2 - 94.2 1991 0.105 - - - - 95.3 1992 0.105 - - - - 96.4 1993 0.090 30.7 65.9 19.4 - 97.7 1994 0.101 - - - - 98.7 1995 0.103 - - - - 100.0 1996 0.060 - - - - 101.0 1997 0.067 34.1 67.4 19.7

  6. Residential energy consumption across different population groups: Comparative analysis for Latino and non-Latino households in U.S.A.

    SciTech Connect (OSTI)

    Poyer, D.A.; Teotia, A.P.S.; Henderson, L.

    1998-05-01

    Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

  7. Buildings Energy Data Book: 2.9 Low-Income Housing

    Buildings Energy Data Book [EERE]

    1 Households Weatherized with ARRA Funds by Grantee (1) Grantee Grantee Alabama Nebraska Alaska Nevada Arizona New Hampshire Arkansas New Jersey California New Mexico Colorado New York Connecticut North Carolina Delaware North Dakota District of Columbia Ohio Florida Oklahoma Georgia Oregon Hawaii Pennsylvania Idaho Rhode Island Illinois South Carolina Indiana South Dakota Iowa Tennessee Kansas Texas Kentucky Utah Louisiana Vermont Maine Virginia Maryland Washington Massachusetts West Virginia

  8. Impact of the FY 2009 Building Technologies Program on United States Employment and Earned Income

    SciTech Connect (OSTI)

    Livingston, Olga V.; Scott, Michael J.; Hostick, Donna J.; Dirks, James A.; Cort, Katherine A.

    2008-06-17

    The Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) is interested in assessing the potential economic impacts of its portfolio of subprograms on national employment and income. A special purpose input-output model called ImSET is used in this study of 14 Building Technologies Program subprograms in the EERE final FY 2009 budget request to the Office of Management and Budget in February 2008. Energy savings, investments, and impacts on U.S. national employment and earned income are reported by subprogram for selected years to the year 2025. Energy savings and investments from these subprograms have the potential of creating a total of 258,000 jobs and about $3.7 billion in earned income (2007$) by the year 2025.

  9. Approaches to Electric Utility Energy Efficiency for Low Income Customers in a Changing Regulatory Environment

    SciTech Connect (OSTI)

    Brockway, N.

    2001-05-21

    As the electric industry goes through a transformation to a more market-driven model, traditional grounds for utility energy efficiency have come under fire, undermining the existing mechanisms to fund and deliver such services. The challenge, then, is to understand why the electric industry should sustain investments in helping low-income Americans use electricity efficiently, how such investments should be made, and how these policies can become part of the new electric industry structure. This report analyzes the opportunities and barriers to leveraging electric utility energy efficiency assistance to low-income customers during the transition of the electric industry to greater competition.

  10. Department of Energy Provides Nearly $112 Million to Low-Income Families

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    for Home Weatherization | Department of Energy 112 Million to Low-Income Families for Home Weatherization Department of Energy Provides Nearly $112 Million to Low-Income Families for Home Weatherization March 29, 2007 - 12:17pm Addthis Funding is First Installment of $204.5 Million in Total Weatherization Grants for FY 2007 WASHINGTON, DC - U.S. Department of Energy (DOE) today announced $111.6 million in weatherization grants to 30 states and the Navajo Nation to make energy efficiency

  11. Low-income energy policy in a restructuring electricity industry: an assessment of federal options

    SciTech Connect (OSTI)

    Baxter, L.W.

    1997-07-01

    This report identifies both the low-income energy services historically provided in the electricity industry and those services that may be affected by industry restructuring. It identifies policies that are being proposed or could be developed to address low- income electricity services in a restructured industry. It discusses potential federal policy options and identifies key policy and implementation issues that arise when considering these potential federal initiatives. To understand recent policy development at the state level, we reviewed restructuring proposals from eight states and the accompanying testimony and comments filed in restructuring proceedings in these states.

  12. Energy Department Provides $140.3 Million to Low-Income Families for Home

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Weatherization | Department of Energy 140.3 Million to Low-Income Families for Home Weatherization Energy Department Provides $140.3 Million to Low-Income Families for Home Weatherization April 3, 2006 - 9:55am Addthis Funding is first installment of $243 million in total weatherization grants for FY 2006 WASHINGTON, D.C. - U.S. Department of Energy (DOE) Secretary Samuel W. Bodman today announced $140.3 million in weatherization program grants to 31 states and the Navajo Nation to make

  13. Evaluation of DOE's Partnership in Low-Income Residential Retrofit (PILIRR) Program

    SciTech Connect (OSTI)

    Callaway, J.W.; Lee, A.D.

    1989-05-01

    In July 1986, the US Department of Energy (DOE) awarded competitive grants to five states to conduct pilot projects to establish partnerships and use resource leveraging to stimulate support for low-income residential energy retrofits. The projects were conducted under DOE's Partnerships in Low-Income Residential Retrofit (PILIRR) Program. These projects have been monitored and analyzed through a concurrent process evaluation conducted by the Pacific Northwest Laboratory (PNL). This study reports the findings of that evaluation. The overriding goal of the PILIRR Program was to determine whether the states could stimulate support for low-income residential energy improvements from non-federal sources. The goal for the process evaluation was to conduct an assessment of the processes used by the states and the extent to which they successfully established partnerships and leveraged resources. Five states were selected to participate in the program: Florida, Iowa, Kentucky, Oklahoma and Washington. Each state proposed a different approach to promote non-federal support for low-income residential weatherization. Three of the five states--Florida, Iowa, and Washington--established partnerships that led to retrofits during the monitoring period (October 1986--October 1988). Kentucky established its partnership during the monitoring period, but did not accomplish its retrofits until after monitoring was complete. Oklahoma completed development of its marketing program and had begun marketing efforts by the end of the monitoring period. 16 refs., 7 figs., 1 tab.

  14. Separate collection of household food waste for anaerobic degradation - Comparison of different techniques from a systems perspective

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2012-05-15

    Highlight: Black-Right-Pointing-Pointer Four modern and innovative systems for household food waste collection are compared. Black-Right-Pointing-Pointer Direct emissions and resource use were based on full-scale data. Black-Right-Pointing-Pointer Conservation of nutrients/energy content over the system was considered. Black-Right-Pointing-Pointer Systems with high energy/nutrient recovery are most environmentally beneficial. - Abstract: Four systems for household food waste collection are compared in relation the environmental impact categories eutrophication potential, acidification potential, global warming potential as well as energy use. Also, a hotspot analysis is performed in order to suggest improvements in each of the compared collection systems. Separate collection of household food waste in paper bags (with and without drying prior to collection) with use of kitchen grinders and with use of vacuum system in kitchen sinks were compared. In all cases, food waste was used for anaerobic digestion with energy and nutrient recovery in all cases. Compared systems all resulted in net avoidance of assessed environmental impact categories; eutrophication potential (-0.1 to -2.4 kg NO{sub 3}{sup -}eq/ton food waste), acidification potential (-0.4 to -1.0 kg SO{sub 2}{sup -}eq/ton food waste), global warming potential (-790 to -960 kg CO{sub 2}{sup -}eq/ton food waste) and primary energy use (-1.7 to -3.6 GJ/ton food waste). Collection with vacuum system results in the largest net avoidance of primary energy use, while disposal of food waste in paper bags for decentralized drying before collection result in a larger net avoidance of global warming, eutrophication and acidification. However, both these systems not have been taken into use in large scale systems yet and further investigations are needed in order to confirm the outcomes from the comparison. Ranking of scenarios differ largely if considering only emissions in the foreground system, indicating the importance of taking also downstream emissions into consideration when comparing different collection systems. The hot spot identification shows that losses of organic matter in mechanical pretreatment as well as tank connected food waste disposal systems and energy in drying and vacuum systems reply to the largest impact on the results in each system respectively.

  15. A Continuous Measure of Gross Primary Production for the Conterminous U.S. Derived from MODIS and AmeriFlux Data

    SciTech Connect (OSTI)

    Xia, Jingfeng; Zhuang, Qianlai; Law, Beverly E.; Chen, Jiquan; Baldocchi, Dennis D.; Cook, David R.; Oren, Ram; Richardson, Andrew D.; Wharton, Sonia; Ma, Siyan; Martin, Timothy A.; Verma, Shashi B.; Suyker, Andrew E.; Scott, Russell L.; Monson, Russell K.; Litvak, Marcy; Hollinger, David Y.; Sun, Ge; Davis, Kenneth J.; Bolstad, Paul V.; Burns, Sean P.; Curtis, Peter S.; Drake, Bert G.; Falk, Matthias; Fischer, Marc L.; Foster, David R.; Gu, Lianhong; Hadley, Julian L.; Katul, Gabriel G.; Matamala, Roser; McNulty, Steve; Meyers, Tilden P.; Munger, J. William; Noormets, Asko; Oechel, Walter C.; U, Kyaw Tha Paw; Schmid, Hans Peter; Starr, Gregory; Torn, Margaret S.; Wofsy, Steven C.

    2009-01-28

    The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000-2004, and was validated using observed GPP over the period 2005-2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km x 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr{sup -1} for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.

  16. Table 2.5 Household Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005

    U.S. Energy Information Administration (EIA) Indexed Site

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space Heating Air Conditioning Water Heating Appliances, 2 Electronics, and Lighting Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Natural Gas Elec- tricity 3 LPG 5 Total Consumption (quadrillion Btu)<//td> 1978 4.26 0.40 2.05 0.23 6.94 0.31 1.04 0.29 0.14 0.06 1.53 0.28 1.46 0.03 1.77 1980 3.41 .27 1.30 .23 5.21 .36 1.15 .30 .22

  17. Process for the utilization of household rubbish or garbage and other organic waste products for the production of methane gas

    SciTech Connect (OSTI)

    Hunziker, M.; Schildknecht, A.

    1985-04-16

    Non-organic substances are separated from household garbage and the organic substances are fed in proportioned manner into a mixing tank and converted into slurry by adding liquid. The slurry is crushed for homogenization purposes in a crushing means and passed into a closed holding container. It is then fed over a heat exchanger and heated to 55/sup 0/ to 60/sup 0/ C. The slurry passes into a plurality of reaction vessels in which the methane gas and carbon dioxide are produced. In a separating plant, the mixture of gaseous products is broken down into its components and some of the methane gas is recycled by bubbling it through both the holding tank and the reaction tank, the remainder being stored in gasholders. The organic substances are degraded much more rapidly through increasing the degradation temperature and as a result constructional expenditure can be reduced.

  18. Emissions of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans from the open burning of household waste in barrels

    SciTech Connect (OSTI)

    Lemieux, P.M.; Lutes, C.C.; Abbott, J.A.; Aldous, K.M.

    2000-02-01

    Backyard burning of household waste in barrels is a common waste disposal practice for which pollutant emissions have not been well characterized. This study measured the emissions of several pollutants, including polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDDs/PCDFs), from burning mixtures designed to simulate waste generated by a recycling and a nonrecycling family in a 208-L (55-gal) burn barrel at the EPA's Open Burning Test Facility. This paper focuses on the PCDD/PCDF emissions and discusses the factors influencing PCDD/PCDF formation for different test burns. Four test burns were made in which the amount of waste placed in the barrel varied from 6.4 to 13.6 kg and the amount actually burned varied from 46.6% to 68.1%. Emissions of total PCDDs/PCDFs ranged between 0.0046 and 0.48 mg/kg of waste burned. Emissions are also presented in terms of 2,3,7,8-TCDD toxic equivalents. Emissions of PCDDs/PCDFs appear to correlate with both copper and hydrochloric acid emissions. The results of this study indicate that backyard burning emits more PCDDs/PCDFs on a mass of refuse burned basis than various types of municipal waste combustors (MWCs). Comparison of burn barrel emissions to emissions from a hypothetical modern MWC equipped with high-efficiency flue gas cleaning technology indicates that about 2--40 households burning their trash daily in barrels can produce average PCDD/PCDF emissions comparable to a 182,000 kg/day (200 ton/day) MWC facility. This study provides important data on a potentially significant source of emissions of PCDDs/PCDFs.

  19. Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations (1994)

    Broader source: Energy.gov [DOE]

    Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations (1994).  Directs each federal agency to make environmental justice part of...

  20. Energy Department Awards $92.5 Million to 19 States to Weatherize Homes of Low-Income Families

    Broader source: Energy.gov [DOE]

    WASHINGTON, DC - Secretary of Energy Samuel W. Bodman announced that $92.5 million has been awarded to 19 states to improve the energy efficiency of low-income family homes. The Department of...